Effects of endurance exercise on the urinary proteome analyzed by 2-D PAGE and Orbitrap MS

Purpose : Exercise‐induced proteinuria is a well‐known phenomenon and the influence of parameters such as intensity and duration was studied extensively. Usually, total protein or albumin was measured for diagnosis of a proteinuria, and the present study was performed to search for qualitative differences in the urinary proteome before and after endurance exercise. Experimental design : Urine samples were concentrated and proteins separated by means of 2‐D PAGE. Proteins differing in the investigated groups were identified by nano‐UPLC‐Orbitrap MS after trypsin digestion. Results : The study yielded several proteins such as hemopexin, albumin, orosomucoid 1, transferrin or carbonic anhydrase 1 that were elevated after a marathon run in comparison to a control group. These are linked to physiological changes resulting from endurance exercise such as destruction of erythrocytes or increased fat metabolism. On the contrary, 2‐D PAGE profiles of athletes at rest did not differ from those of control samples. Conclusions and clinical relevance: The study is a starting point to build up individual 2‐D PAGE protein maps of athletes. Further studies will investigate intra‐individual differences and further exercise parameters, which potentially lead to a physiological monitoring system for athletes in training and competition and may also complement the blood passport in doping control.     

Shotgun proteomics identifies proteins specific for acute renal transplant rejection

Purpose: Acute rejection (AR) remains the primary risk factor for renal transplant outcome; development of non‐invasive diagnostic biomarkers for AR is an unmet need. Experimental design: We used shotgun proteomics applying LC‐MS/MS and ELISA to analyze a set of 92 urine samples, from patients with AR, stable grafts (STA), proteinuria (NS), and healthy controls. Results: A total of 1446 urinary proteins (UP) were identified along with a number of non‐specific proteinuria‐specific, renal transplantation specific and AR‐specific proteins. Relative abundance of identified UP was measured by protein‐level spectral counts adopting a weighted fold‐change statistic, assigning increased weight for more frequently observed proteins. We have identified alterations in a number of specific UP in AR, primarily relating to MHC antigens, the complement cascade and extra‐cellular matrix proteins. A subset of proteins (uromodulin, SERPINF1 and CD44), have been further cross‐validated by ELISA in an independent set of urine samples, for significant differences in the abundance of these UP in AR. Conclusions and clinical relevance: This label‐free, semi‐quantitative approach for sampling the urinary proteome in normal and disease states provides a robust and sensitive method for detection of UP for serial, non‐invasive clinical monitoring for graft rejection after kidney transplantation.     

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

Inherent to the biomarker discovery process is a comparative analysis of physiological states. It is therefore critical that the proteome detection protocol does not bias the analysis. With urine, the sediment portion, obtained upon thawing frozen urine, is routinely discarded prior to proteome analysis. However, our results demonstrate that such a practice inadvertently induces bias, having significant implications in the biomarker discovery process. We present the first proteome investigation of human urinary sediments, identifying 60 proteins in this phase by MS. Many sediment proteins were also detected in the urinary supernatant, indicating that several proteins partition between the two phases. This partitioning is dependant on the pH of the sample, as well as the degree of sample agitation. As a consequence of discarding the sediment portion of urine, the concentration of potential candidate biomarkers in the supernatant phase will be altered or, in other instances, may be completely removed from the sample. To minimize this, the pH of all samples should first be normalized, and the samples vigorously vortexed prior to discarding the sediments. For more comprehensive biomarker investigations, we suggest that urinary sediments be analyzed along with the supernatant proteins.     

Discovery of putative oocyte quality markers by comparative ExacTag proteomics

Purpose: Identification of the biomarkers of oocyte quality, and developmental and reprogramming potential is of importance to assisted reproductive technology in humans and animals. Experimental design: PerkinElmer ExacTag? Kit was used to label differentially proteins in pig oocyte extracts (oocyte proteome) and pig oocyte‐conditioned in vitro maturation media (oocyte secretome) obtained with high‐ and low‐quality oocytes. Results: We identified 16 major proteins in the oocyte proteome that were expressed differentially in high‐ versus low‐quality oocytes. More abundant proteins in the high‐quality oocyte proteome included kelch‐like ECH‐associated protein 1 (an adaptor for ubiquitin‐ligase CUL3), nuclear export factor CRM1 and ataxia‐telangiectasia mutated protein kinase. Dystrophin (DMD) was more abundant in low‐quality oocytes. In the secretome, we identified 110 proteins, including DMD and cystic fibrosis transmembrane conductance regulator, two proteins implicated in muscular dystrophy and cystic fibrosis, respectively. Monoubiquitin was identified in the low‐quality‐oocyte secretome. Conclusions and clinical implications: A direct, quantitative proteomic analysis of small oocyte protein samples can identify potential markers of oocyte quality without the need for a large amount of total protein. This approach will be applied to discovery of non‐invasive biomarkers of oocyte quality in assisted human reproduction and in large animal embryo transfer programs.     

Profiling of rat urinary proteomic patterns associated with drug-induced nephrotoxicity using CE coupled with MS as a potential model for detection of drug-induced adverse effects

We have investigated urine obtained from Sprague Dawley rats before and after administration of cis-Platin, aiming at the definition of biomarkers for drug-induced cytotoxicity. Rats were treated with 3 or 6 mg/kg cis-Platin (i.p., single injection) and urine samples were collected before and after drug or saline treatment. Analysis of the low molecular weight proteome (<20 kDa) using capillary-electrophoresis coupled mass spectrometry allowed us to tentatively identify 34 urinary peptides that show significant differences between control and treated animals, and hence may serve as a potential biomarker for cis-Platin-induced nephrotoxicity. These biomarkers were confirmed in a blinded assessment of additional samples. The blinded data also revealed time-dependency of induced changes. Some of the potential biomarkers could be sequenced. This information revealed great similarity between cis-Platin-induced changes and significant changes in the urinary proteome of patients suffering from tubular injury (Fanconi syndrome). Our study strongly suggests that (drug-induced) nephrotoxicity can be detected with high accuracy in laboratory rodents using urinary proteome analysis. The effects observed are very similar to those seen in corresponding human diseases and similar approaches may be very helpful in evaluating drug-induced organ damage in preclinical animal models. This study aiming at the definition of biomarkers for drug-induced cytotoxicity may serve as a proof-of-principle for the use of urinary proteomics in assessment of drug-induced nephrotoxicity.     

Implementation of Proteomics Biomarkers in Nephrology: From Animal Models to Human Application?

Preclinical animal models are extensively used in nephrology. In this review, the utility of performing proteome analysis of kidney tissue or urine in such models and transfer of the results to human application has been assessed. Analysis of the literature identified 68 relevant publications. Pathway analysis of the reported proteins clearly indicated links with known biological processes in kidney disease providing validation of the observed changes in the preclinical models. However, although most studies focused on the identification of early markers of kidney disease or prediction of its progression, none of the identified makers has made it to substantial validation in the clinic or at least in human samples. Especially in renal disease where urine is an abundant source of biomarkers of diseases of the kidney and the urinary tract, it therefore appears that the focus should be on human material based discovery studies. In contrast, the most valid information of proteome analysis of preclinical models in nephrology for translation in human disease resides in studies focusing on drug evaluation, both efficacy for translation to the clinic and for mechanistic insight.     

Non-invasive biomarker sampling and analysis of the exhaled breath proteome

Exhaled breath condensate (EBC) is a biological fluid that contains trace amounts of secreted pulmonary proteins, and is emerging as a potentially valuable and non-invasively obtained source of disease biomarkers. Proteome analysis of these samples could lead to the identification of prognostic indicators of airway diseases. The objective of this study was to develop a protocol for proteome analysis of EBC samples. In this report, an improved procedure for EBC sample preparation and concentration is presented, together with a method for comparison of the protein profiles between two groups. The presented approach enabled to study the condensed exhaled breath proteome for biomarker analysis, and revealed proteins not previously identified in an EBC proteomics approach. In a comparative pilot study, EBC protein profiles obtained from smokers and non-smokers showed distinct differences and are illustrative for its potential in clinical studies. EBC from smokers contained higher concentrations of the more abundant proteins, such as cytokeratins, compared to non-smokers, and calgranulin B was identified uniquely in EBC samples from smokers.     

Mapping the 5-50-kDa fraction of human amniotic fluid proteins by 2-DE and ESI-MS

This report presents a proteomic analysis and provides a reference map of the 5-50-kDa components of normal amniotic fluid collected in gestational weeks 16-18. Early amniocentesis samples were pooled and proteins with molecular mass lower than albumin were separated by gel filtration chromatography. The 2-DE protocol was optimized for the separation of the small proteins and peptides in the fraction of interest. A total of 132 Coomassie blue-stained protein spots were analyzed, following in-gel tryptic digestion, by ESI-MS/MS and 49 different gene products were identified. The treatment with alkaline phosphatase caused the shift of the phosphoisoforms of insulin-like growth factor-binding protein-1 and of the N-terminal osteopontin fragment. Of the 33 full-length proteins identified in the 2-DE profile, 23 had not been previously detected in the amniotic fluid and, of these, 22 are not present in the human plasma proteome under physiological conditions. Fragments of 16 larger proteins were identified and the sequence coverage data revealed that several correspond to autonomous domains that may have biological roles on their own. Several of the detected proteins and peptides appear to be involved in critical regulatory processes associated with placentation and early development, thus representing potential markers of various physiological or pathological conditions.     

Urinary proteomics in cardiovascular disease: Achievements, limits and hopes

Cardiovascular disease (CVD) is the major cause of mortality and morbidity worldwide. Diagnosis of CVD and risk stratification of patients with CVD remains challenging despite the availability of a wealth of non-invasive and invasive tests. Clinical proteomics analyses a large number of peptides and proteins in biofluids. For clinical applications, the urinary proteome appears particularly attractive due to the relative low complexity compared with the plasma proteome and the noninvasive collection of urine. In this article, we review the results from pilot studies into urinary proteomics of coronary artery disease and discuss the potential of urinary proteomics in the context of pathogenesis of CVD.     

Towards a comprehensive proteome of normal and malignant human colon tissue by 2-D-LC-ESI-MS and 2-DE proteomics and identification of S100A12 as potential cancer biomarker

The aim of this study was to characterize the proteome of normal and malignant colonic tissue. We previously studied the colon proteome using 2‐DE and MALDI‐MS and identified 734 proteins (Roeßler, M., Rollinger, W., Palme S., Hagmann, M.‐L., et al.., Clin. Cancer Res. 2005, 11, 6550–6557). Here we report the identification of additional colon proteins from the same set of tissue samples using a complementary nano‐flow 2‐D‐LC‐ESI‐MS. In total, 484 proteins were identified in colon. Of these, 252 had also been identified by the 2‐DE/MALDI‐MS approach, whereas 232 proteins were unique to the 2‐D‐LC‐ESI‐MS analysis. Comparing protein expression in neoplastic and normal colon tissue indicated elevated expression of several proteins in colorectal cancer, among them the well established tumor marker carcinoembryonic antigen, as well as calnexin, 40S ribosomal protein S15a, serpin H1, and S100A12. Overexpression of these proteins was confirmed by immunoblotting. Serum levels of S100A12 were determined by ELISA and were found to be strongly elevated in colorectal cancer patients compared to healthy individuals. We conclude, that 2‐D‐LC‐ESI‐MS is a powerful approach to identify and compare protein profiles of tissue samples, that it is complementary to 2‐DE/MALDI‐MS approaches and has the potential to identify novel biomarkers.     

Proteomic analysis of serum, plasma, and lymph for the identification of biomarkers

Probably no topic has generated more excitement in the world of proteomics than the search for biomarkers. This excitement has been generated by two realities: the constant need for better biomarkers that can be used for disease diagnosis and prognosis, and the recent developments in proteomic technologies that are capable of scanning the individual proteins within varying complex clinical samples. Ideally a biomarker would be assayable from a noninvasively collected sample, therefore, much of the focus in proteomics has been on the analysis of biofluids such as serum, plasma, urine, cerebrospinal fluid, lymph, etc. While the discovery of biomarkers has been elusive, there have been many advances made in the understanding of the proteome content of various biofluids, and in the technologies used for their analysis, that continues to point the research community toward new methods for achieving the ultimate goal of identifying novel disease-specific biomarkers. In this review, we will describe and discuss many of the proteomic approaches taken in an attempt to find novel biomarkers in serum, plasma, and lymph.     

Identification of proteins in human substantia nigra

Characterization of the human brain proteome is a critical area of research. While examination of the human cortex has provided some insight, very little is known about the proteome of the human midbrain, which demonstrates substantial loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc) in Parkinson's disease (PD). Therefore, characterization of this region is essential to a better understanding of the pathogenesis of PD. This dataset paper reports two separate studies, where human SNpc was collected from PD and control subjects and 1263 proteins were identified using MALDI-TOF/TOF as well as linear ion trap MS platforms. With gene ontology analysis, the proteins were categorized according to their biological processes, as well as cellular components. These data were also compared with previous proteomic characterization of the human frontal and temporal cortex, and cerebrospinal fluid to establish shared proteins of relevance. The present dataset is the most extensive survey of the human SNpc proteome, to date. Further characterization of the SNpc proteome will significantly facilitate our understanding of the function and expression of proteins involved in PD, as well as provide potential proteins that may be utilized as biomarkers.     

Evaluation of a type 1 diabetes serum cohort by SELDI-TOF MS protein profiling

Proteomics analysis of serum from patients with type 1 diabetes (T1D) may lead to novel biomarkers for prediction of disease and for patient monitoring. However, the serum proteome is highly sensitive to sample processing and before proteomics biomarker research serum cohorts should preferably be examined for potential bias between sample groups. SELDI‐TOF MS protein profiling was used for preliminary evaluation of a biological‐bank with 766 serum samples from 270 patients with T1D, collected at 18 different paediatric centers representing 15 countries in Europe and Japan over 2 years (2000–2002). Samples collected 1 (n = 270), 6 (n = 248), and 12 (n = 248) months after T1D diagnosis were grouped across centers and compared. The serum protein profiles varied with collection site and day of analysis; however, markers of sample processing were not systematically different between samples collected at different times after diagnosis. Three members of the apolipoprotein family increased with time in patient serum collected 1, 6, and 12 months after diagnosis (ANOVA, p<0.001). These results support the use of this serum cohort for further proteomic studies and illustrate the potential of high‐throughput MALDI/SELDI‐TOF MS protein profiling for evaluation of serum cohorts before proteomics biomarker research.     

Large-scale protein identification of human urine proteome by multi-dimensional LC and MS/MS

Urine is a human specimen that is easily obtained non-invasively for clinical diagnosis. We attempted to enhance the resolution of current human urine proteomes and construct a comprehensive reference database for advanced studies, such as the discovery of biomarkers for renal diseases. Multi-dimensional LC-MS/MS was coupled with de novo sequencing and database matching. The proposed approach improved the identification of not only the proteins, but also the post-translational sites of urinary proteins. We identified 165, 200 and 259 unique gene products in the urine proteomes from males, females and pregnant women, respectively. When all of the results were combined and the redundancies removed, a total of 1095 distinct peptides were identified. Of these, 1016 peptides were associated with 334 unique gene products. In this study, over 100 gene products, including some disease-related proteins, were detected in urine for the first time by proteomic approaches. Various proteins with novel post-translational hydroxylation were identified using the MASCOT program and de novo sequencing. All proteins with peptide information were summarized into a comprehensive urine protein database. We believe that this comprehensive urine proteome database will assist in the identification of urinary proteins/polypeptides whose spectra are difficult to interpret in the discovery of urinary biomarkers.     

Proteomic profile of differentially expressed plasma proteins from dystrophic mice and following suberoylanilide hydroxamic acid treatment

Purpose: Histone Deacetylase Inhibitors (DI) ameliorates dystrophic muscle regeneration restoring muscular strength in the mdx mouse model of Duchenne muscular dystrophy (DMD). The further development of these compounds as drugs for DMD treatment is currently hampered by the lack of knowledge about DIs effect in large dystrophic animal models and that of suitable biomarkers to monitor their efficacy. Experimental design: In this study we applied proteomic analysis to identify differentially expressed proteins present in plasma samples from mdx mice treated with the Suberoylanilide hydroxamic acid (SAHA) and relative normal controls (WT). Results: Several differentially expressed proteins were identified between untreated wild type and mdx mice. Among these, fibrinogen, epidermal growth factor 2 receptor, major urinary protein and glutathione peroxidase 3 (GPX3) were constitutively up‐regulated in mdx, while complement C3, complement C6, gelsolin, leukaemia inhibitory factor receptor (LIFr), and alpha 2 macroglobulin were down‐regulated compared to WT mice. SAHA determined the normalization of LIFr and GPX3 protein level while apoliprotein E was de novo up‐regulated in comparison to vehicle‐treated mdx mice. Conclusions and clinical relevance: Collectively, these data unravel potential serological disease biomarkers of mdx that could be useful to monitor muscular dystrophy response to DI treatment.     

Proteomic analysis for human urinary proteins associated with arsenic intoxication

Arsenic is widely distributed in nature and is mainly transported in the environment by water. Consumption of artesian well water with high levels of arsenic has been associated with genitourinary cancer, especially bladder transitional cell carcinoma (TCC). To search for biomarkers that are specific for arsenic associated with the diagnosis of bladder TCC, proteins in the urine of non-cancer urological patients and patients with either bladder TCC or arsenic-associated bladder TCC were systematically examined by HPLC ESI-MS/MS. Urine specimens were collected by catheterization from patients and age- (within 5?years) and sex-matched non-cancer urological patients. A nano-HPLC-ESI-MS/MS was used to generate proteome patterns from urine specimens obtained from patients with arsenic-associated (n?=?8) and non-arsenic-associated (n?=?8) primary TCC and from sex- and age-matched non-cancer urological patients (n?=?8). Three urinary proteins were found to have significantly altered levels in patients following chronic arsenic exposure. These proteins were a disintegrin and metalloprotease (ADAM) protein, a calpain9, and ring finger protein 20. The large-scale identification of urinary proteomes using HPLC ESI-MS/MS may serve as an ideal and efficient method to establish a panel of potential arsenic-associated TCC biomarkers and may help elucidate the mechanisms involved in bladder cancer induced by chronic arsenic exposure.     

Aberrant protein expression in plasma and kidney tissue during experimental obstructive nephropathy

Kidney failure is a major health problem worldwide. Patients with end-stage renal disease require intensive medical support by dialysis or kidney transplantation. Current methods for diagnosis of kidney disease are either invasive or insensitive, and renal function may decline by as much as 50% before it can be detected using current techniques. The goal of this study was, therefore, to identify biomarkers of kidney disease (associated with renal fibrosis) that can be used for the development of a non-invasive clinical test for early disease detection. We utilized two protein-profiling technologies (SELDI-TOF MS and 2-D) to screen the plasma and kidney proteome for aberrantly expressed proteins in an experimental mouse model of unilateral uretric obstruction, which mimics the pathology of human renal disease. Several differentially regulated proteins were detected at the plasma level of day-3-obstructed animals, which included serum amyloid A1, fibrinogen α, haptoglobin precursor protein, haptoglobin and major urinary proteins 11 and 8. Differentially expressed proteins detected at the tissue level included ras-like activator protein 2, haptoglobin precursor protein, malate dehydrogenase, α enolase and murine urinary protein (all p<0.05 versus controls). Immunohistochemistry was used to confirm the up-regulation of fibrinogen. Interestingly, these proteins are largely separated into four major classes: (i) acute-phase reactants (ii) cell-signaling molecules (iii) molecules involved in cell growth and metabolism and (iv) urinary proteins. These results provide new insights into the pathology of obstructive nephropathy and may facilitate the development of specific assay(s) to detect and monitor renal fibrosis.     

Microfiltration isolation of human urinary exosomes for characterization by MS

Purpose: The purpose of this study was to address the hypothesis that small vesicular urinary particles known as exosomes could be selectively microfiltered using low protein‐binding size exclusion filters, thereby simplifying their use in clinical biomarker discovery studies. Experimental design: We characterized a microfiltration approach using a low protein binding, hydrophilized polyvinylidene difluoride membrane to easily and efficiently isolate urinary exosomes from fresh, room temperature or 4°C urine, with a simultaneous depletion of abundant urinary proteins. Using LC‐MS, immunoblot analysis, and electron microscopy methods, we demonstrate this method to isolate intact exosomes and thereby enrich for a low abundant urinary proteome. Results: In comparison to other standard methods of exosome isolation including ultracentrifugation and nanofiltration, we demonstrate equivalent enrichment of the exosome proteome with reduced co‐purification of abundant urinary proteins. Conclusion and clinical relevance: In conclusion, we demonstrate a microfiltration isolation method that preserves the exosome structure, reduces contamination from higher abundant urinary proteins, and can be easily implemented into mass spectrometry analysis for biomarker discovery efforts or incorporation into routine clinical laboratory applications to yield higher sample throughput.     

Exosomes in bodily fluids are a highly stable resource of disease biomarkers

Biomarkers are measurable indicators of a biological state. As our understanding of diseases meliorates, it is generally accepted that early diagnosis renders the best chance to cure a disease. In the context of proteomics, the discovery phase of identifying bonafide biomarkers and the ensuing validation phase involving large cohort of patient samples are impeded by the complexity of bodily fluid samples. High abundant proteins found in blood plasma make it difficult for the detection of low abundant proteins that may be potential biomarkers. Extracellular vesicles (EVs) have reignited interest in the field of biomarker discovery. EVs contain a tissue-type signature wherein a rich cargo of proteins and RNA are selectively packaged. In addition, as EVs are membranous structures, the luminal contents are protected from degradation by extracellular proteases and are highly stable in storage conditions. Interestingly, an appealing feature of EV-based biomarker analysis is the significant reduction in the sample complexity compared to whole bodily fluids. With these prescribed attributes, which are the rate-limiting factors of traditional biomarker analysis, there is immense potential for the use of EVs for biomarker detection in clinical settings. This review will discuss the current issues with biomarker analysis and the potential use of EVs as reservoirs of disease biomarkers.     

Considerations for powering a clinical proteomics study: Normal variability in the human plasma proteome

Proteomics is increasingly being applied to the human plasma proteome to identify biomarkers of disease for use in non‐invasive assays. 2‐D DIGE, simultaneously analysing thousands of protein spots quantitatively and maintaining protein isoform information, is one technique adopted. Sufficient numbers of samples must be analysed to achieve statistical power; however, few reported studies have analysed inherent variability in the plasma proteome by 2‐D DIGE to allow power calculations. This study analysed plasma from 60 healthy volunteers by 2‐D DIGE. Two samples were taken, 7 days apart, allowing estimation of sensitivity of detection of differences in spot intensity between two groups using either a longitudinal (paired) or non‐paired design. Parameters for differences were: two‐fold normalised volume change, α of 0.05 and power of 0.8. Using groups of 20 samples, alterations in 1742 spots could be detected with longitudinal sampling, and in 1206 between non‐paired groups. Interbatch gel variability was small relative to the detection parameters, indicating robustness and reproducibility of 2‐D DIGE for analysing large sample sets. In summary, 20 samples can allow detection of a large number of proteomic alterations by 2‐D DIGE in human plasma, the sensitivity of detecting differences was greatly improved by longitudinal sampling and the technology was robust across batches.