Proteomic analysis of a podocyte vesicle-enriched fraction from human normal and pathological urine samples

Podocytes (glomerular visceral epithelial cells) release vesicles into urine. Podocyte vesicle-enriched fractions from normal and pathological human urine samples were prepared for proteomic analysis. An immunoadsorption method was applied and enrichment of podocyte vesicles was assessed. We identified 76 unique proteins. One protein, serum paraoxonase/arylesterase 1 (PON-1), was newly identified in normal human urine sample. We confirmed this result and showed PON-1 expression in normal human kidney. These results demonstrated the potential for using the urine samples enriched in podocyte vesicles as a starting material in studies aimed at discovery of biomarkers for diseases.     

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.     

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.     

蛋白质数据库中匹配间隙序列标签的自动机算法

对于肽和蛋白质的分析鉴别,串联质谱（MS／MS）是极其重要的方法。解释MS／MS数据的一种方法是de novo序列,它正变得越来越准确和重要了。但de novo序列通常只能准确地判定序列的一部分,而对于不确定的部分只能通过“质量间隙”来表示,我们称这样部分确定的序列为间隙序列标签。对于蛋白质的分析鉴别,当在数据库中查询一个间隙序列标签时,其中确定的部分应与数据库蛋白质序列完全匹配,而对于每一个质量间隙也应匹配一个氨基酸子串,这些氨基酸子串的质量和应与质量间隙的质量和相等。在这种情况之下,标准的串匹配算法已经不再适用。在本文中,我们将提出一个新的且有效的算法,用以在蛋白质数据库中找到与间隙序列标签所匹配的序列。     

Proteomics of Alzheimer's disease: Unveiling protein dysregulation in complex neuronal systems

Alzheimer's disease (AD) and its progressive dementia is multifactorial, develops relatively sporadically, and involves multiple pathologies in the complex biological system of the brain. For these reasons, genetics alone is not likely to explain the molecular basis of this disease. Proteomics is contributing valuable information about the underlying molecular defects involved in AD development and progression, which includes oxidative damage to specific proteins, altered levels of synaptic components, and protein compositions of Aβ plaques and neurofibrillary tangles (pathological hallmarks of AD). However, emerging strategies in the field of proteomics which include more specific targeting of disease-related anatomical regions, targeting of specific subcellular compartments of functional relevance, novel approaches for large scale identification of regulatory post-translational modifications such as phosphorylation and O-GlcNAc, improved chromatographic separations of peptides for more comprehensive analysis of samples, and high-throughput quantitative strategies directly coupled with MS should greatly enhance the future of AD proteomics. The characterization of AD-specific alterations in proteomes should provide further insight into mechanisms of disease development and progression, provide biomarkers predicting disease development, and provide novel targets for therapeutic intervention.     

Urine proteomics for profiling of human disease using high accuracy mass spectrometry

Knowledge of the biologically relevant components of human tissues has enabled the invention of numerous clinically useful diagnostic tests, as well as non-invasive ways of monitoring disease and its response to treatment. Recent use of advanced MS-based proteomics revealed that the composition of human urine is more complex than anticipated. Here, we extend the current characterization of the human urinary proteome by extensively fractionating urine using ultra-centrifugation, gel electrophoresis, ion exchange and reverse-phase chromatography, effectively reducing mixture complexity while minimizing loss of material. By using high-accuracy mass measurements of the linear ion trap-Orbitrap mass spectrometer and LC-MS/MS of peptides generated from such extensively fractionated specimens, we identified 2362 proteins in routinely collected individual urine specimens, including more than 1000 proteins not described in previous studies. Many of these are biomedically significant molecules, including glomerularly filtered cytokines and shed cell surface molecules, as well as renally and urogenitally produced transporters and structural proteins. Annotation of the identified proteome reveals distinct patterns of enrichment, consistent with previously described specific physiologic mechanisms, including 336 proteins that appear to be expressed by a variety of distal organs and glomerularly filtered from serum. Comparison of the proteomes identified from 12 individual specimens revealed a subset of generally invariant proteins, as well as individually variable ones, suggesting that our approach may be used to study individual differences in age, physiologic state and clinical condition. Consistent with this, annotation of the identified proteome by using machine learning and text mining exposed possible associations with 27 common and more than 500 rare human diseases, establishing a widely useful resource for the study of human pathophysiology and biomarker discovery.     

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.     

Proteins and protein fragments in nephrotic syndrome: Clusters, specificity and mechanisms

Proteinuria is the hallmark of renal diseases and the characterization of the urinary protein composition may become an important source of information for diagnosis and research. So far, protein analysis in urine has been utilized for a generic individuation of site-specific defects (glomerular vs. tubular) but there is a need for an extension of proteomics to specific urinary biomarkers in selected clinical conditions. The identification of fragments of proteins in plasma and urine may increase the spectrum of urinary biomarkers. The unique speculative application so far proposed for protein fragments is nephrotic syndrome, and specifically focal segmental glomerulosclerosis, in which case they reflect intrinsic proteolysis occurring in plasma and represent surrogate biomarkers of the disease activity. Albumin is probably the most studied protein. Several of the albumin fragments present a peculiar distribution of the fingerprint peptide pattern containing both the N-terminal region and the C-terminal domain with a complete lack of any MS signals for the internal sequence region. Their characterization utilizing new strategies based on 2-D nondenaturing electrophoresis is now in progress. Studies on a direct characterization of proteases in plasma and urine will also define the participation of proteases to the genesis of renal diseases.     

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.     

Clinical applications of capillary electrophoresis coupled to mass spectrometry in biomarker discovery: Focus on bladder cancer

A major requirement in the application of proteins as clinical biomarkers is that they provide a highly sensitive and specific result in disease assessment. Since single biomarkers are generally of limited accuracy, a group or panel of well-characterized biomarkers appears appropriate, providing a more robust and sensitive MS-based analytical platform. CE coupled to MS has been successfully used in biomarker discovery and application, as it enables the selective detection of peptides and small proteins, combining the high separation capacity of CE with the advanced sensitivity of MS. CE-MS allows the characterization of highly complex samples (such as urine, plasma, and other biofluids) in a consistent and reproducible way. It has a range of applications, many focusing especially in studies on urinary peptide biomarkers in kidney and cardiovascular diseases. Another major field of interest has been malignancy of the genitourinary system. In the first part of this review, we cover technical aspects and performance characteristics of CE-MS, with special focus on the requirements for biomarker discovery and clinical application. In the second part, we review the potential and development of CE-MS in the management of genitourinary cancers, especially bladder cancer. CE-MS has been employed in several studies aimed at discovering biomarkers for bladder cancer that may be useful in diagnosis, monitoring for recurrence, and prediction of the risk for the muscle-invasive stage. In the last part of the review, we discuss current challenges and provide an outlook for ongoing and possible future developments.     

MS analysis of rheumatoid arthritic synovial tissue identifies specific citrullination sites on fibrinogen

Purpose : Citrullination is a post‐translational modification of arginine residues to citrulline catalyzed by peptidyl arginine deiminases. Induced expression of citrullinated proteins are frequently detected in various inflammatory states including arthritis; however, direct detection of citrullination in arthritic samples has not been successfully performed in the past. Experimental design : Citrullination of human fibrinogen, a candidate autoantigen in arthritis, was studied. Accurate identification of citrullinated fibrinogen peptides from rheumatoid arthritis synovial tissue specimens was performed using accurate mass and retention time analysis. Results : A peptide with the sequence ESSSHHPGIAEFPSRGK corresponding to amino acids 559–575 of fibrinogen α‐chain was identified to be citrullinated with an occupancy rate between 1.4 and 2.5%. Citrullination of the peptide KREEAPSLRPAPPPISGGGYRARPAK corresponding to amino acids 52–77 of the fibrinogen β‐chain was identified with an occupancy rate of 1.2%. Conclusions and clinical relevance : We report a proof of principle study for the identification of citrullinated proteins and within them, identification of citrullination sites and quantification of their occupancies in synovial tissue from rheumatoid arthritis patients using high‐resolution MS. Detailed studies on which molecules are citrullinated in arthritis can provide information about their role in immune regulation and serve as novel biomarkers and potentially even as therapeutic targets.     

Discovery of diagnostic serum biomarkers of gastric cancer using proteomics

Gastric cancer has significant morbidity and mortality worldwide and locally. Good prognosis relies on an early diagnosis. However, this remains a challenge due to the lack of specific and sensitive serum biomarkers for early detection. Hence, there is a constant search for these biomarkers for screening purposes. Proteomic profiling enables a new approach to the discovery of biomarkers in disease. This review presents recent attempts in search of gastric cancer serum biomarker using proteomics. Different methodologies and different types of samples were employed by different groups of researchers. Major difficulties were encountered in the discovery processes, including interference from abundant proteins and continuous changing serum proteomes from different individuals.     

Urine proteomics in kidney and urogenital diseases: Moving towards clinical applications

To date, multiple biomarker discovery studies in urine have been conducted. Nevertheless, the rate of progression of these biomarkers to qualification and even more clinical application is extremely low. The scope of this article is to provide an overview of main clinically relevant proteomic findings from urine focusing on kidney diseases, bladder and prostate cancers. In addition, approaches for promoting the use of urine in clinical proteomics including potential means to facilitate the validation of existing promising findings (biomarker candidates identified from previous studies) and to increase the chances for success for the identification of new biomarkers are discussed.     

Sub-proteome approach to the knowledge of liver

In the recent years, global proteomics approaches have been widely used to characterize a number of tissue proteomes including plasma and liver; however, the elevated complexity of these samples in combination with the high abundance of some specific proteins make the study of the lowest abundant proteins difficult. This review is focused on different strategies that have been developed to extend the proteome focused on these two tissues, as, for example, the analysis of sub-cellular proteomes. In this regard, two special kind of extracellular vesicles--exosomes and membrane plasma shedding vesicles--are emerging as excellent biological source both to extend the liver and plasma proteomes and to be applied in the discovery of non-invasive liver-specific disease biomarkers.     

Analysis of biofluids for biomarker research

While many of the developments made in high-throughput proteomics were originally applied to procaryotic and simple eucaryotic organisms, the analysis of biofluids became increasingly important as the prospect of using proteomics to discover novel biomarkers became realized. Biofluids have represented a unique challenge to proteomics as they are often present only in small amounts and, particularly in the cases of serum and plasma, can have protein concentration ranges that differ by ten orders of magnitude. While the discovery of authentic, clinically useful biomarkers in the proteomics era has been lacking, there have been a number of significant developments in the ability to more comprehensively characterize biofluid proteomes. The rapid pace of these developments suggest that the eventual discovery of clinically validate biomarkers using proteomic technologies still has a bright future.     

Profiling the proteome in renal transplantation

Improved monitoring of transplanted solid organs is one of the next crucial steps leading to an increase in both patient and allograft survival. This can be facilitated through one or a set of surrogate biomarker molecules that accurately and precisely indicate the health status of the transplanted organ. Recent developments in the field of high throughput "omic" methods including genomics and proteomics have facilitated robust and comprehensive analysis of genes and proteins. This development has stimulated efforts in the identification of effective and clinically applicable gene and protein biomarkers in solid organ transplantation, including kidney transplantation. Some achievements have been made through proteomics in terms of profiling proteins and identification of potential biomarkers. However, the road to a successful biomarker discovery and its clinical implementation has proved to be challenging, requiring a number of key issues to be addressed. Such issues are: the lack of widely accepted protocols, difficulty in sample processing and transportation and a lack of collaborative efforts to achieve significant sample sizes in clinical studies. In this review using our area of expertise, we describe the current strategies used for proteomic-based biomarker discovery in renal transplantation, discuss inherent issues associated with these efforts and propose better strategies for successful biomarker discovery.     

基于图卷积神经网络的串联质谱从头测序

在蛋白质组学中从头测序是串联质谱肽段测序的重要方法之一，其具有不依赖于蛋白质数据库的优势，并在测定未知物种蛋白序列、单克隆抗体测序等领域中起着关键作用。然而由于从头测序的复杂性，导致其测序的准确率远低于数据库搜索方法，制约了从头测序的广泛应用。针对从头测序准确率低的问题，提出一种基于图卷积神经网络（GCN）的从头测序方法denovo-GCN。该方法将质谱中谱峰之间的关系用图结构表示，并从每个相应的肽碎裂位点提取谱峰特征，然后通过GCN预测当前碎裂位点处的氨基酸类型，最后逐步组成完整的肽序列。通过实验确定了GCN模型的层数、离子类型组合和测序使用的谱峰数量这3个影响模型的重要参数，并将多个物种数据集用于实验对比。实验结果表明，该方法在肽水平上的召回率比基于图论的从头测序方法Novor、pNovo提高了4.0~21.1个百分点，比基于卷积神经网络（CNN）和长短期记忆（LSTM）网络的DeepNovo提高了2.1~10.7个百分点。