Practical points in urinary proteomics

During the proteomic era, one of the most rapidly growing areas in biomedical research is biomarker discovery, particularly using proteomic technologies. Urinary proteomics has become one of the most attractive subdisciplines in clinical proteomics, as the urine is an ideal source for the discovery of noninvasive biomarkers for human diseases. However, there are several barriers to the success of the field and urinary proteome analysis is not a simple task because the urine has low protein concentration, high levels of salts or other interfering compounds, and more importantly, high degree of variations (both intra-individual and inter-individual variabilities). This article provides step-by-step practical points to perform urinary proteome analysis, covering detailed information for study design, sample collection, sample storage, sample preparation, proteomic analysis, and data interpretation. The discussion herein should stimulate further discussion and refinement to develop guidelines and standardizations for urinary proteome study.     

Investigation of the mouse serum proteome

With the rapid assimilation of genomic information and the equally impressive developments in the field of proteomics, there is an unprecedented interest in biomarker discovery. Although human biofluids represent increasingly attractive samples from which new and more accurate disease biomarkers may be found, the intrinsic person-to-person variability in these samples complicates their discovery. One of the most extensively used animal models for studying human disease is mouse because, unlike humans, they represent a highly controllable experimental model system. Unfortunately, very little is known about the proteomic composition of mouse serum. In this study, a multidimensional fractionation approach on both the protein and the peptide level that does not require depletion of highly abundant serum proteins was combined with tandem mass spectrometry to characterize proteins within mouse serum. Over 12 300 unique peptides that originate from 4567 unique proteins-approximately 16% of all known mouse proteins-were identified. The results presented here represent the broadest proteome coverage in mouse serum and provide a foundation from which quantitative comparisons can be made in this important animal model.     

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 ).     

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.     

Advances and challenges in liquid chromatography-mass spectrometry-based proteomics profiling for clinical applications

Recent advances in proteomics technologies provide tremendous opportunities for biomarker-related clinical applications; however, the distinctive characteristics of human biofluids such as the high dynamic range in protein abundances and extreme complexity of the proteomes present tremendous challenges. In this review we summarize recent advances in LC-MS-based proteomics profiling and its applications in clinical proteomics as well as discuss the major challenges associated with implementing these technologies for more effective candidate biomarker discovery. Developments in immunoaffinity depletion and various fractionation approaches in combination with substantial improvements in LC-MS platforms have enabled the plasma proteome to be profiled with considerably greater dynamic range of coverage, allowing many proteins at low ng/ml levels to be confidently identified. Despite these significant advances and efforts, major challenges associated with the dynamic range of measurements and extent of proteome coverage, confidence of peptide/protein identifications, quantitation accuracy, analysis throughput, and the robustness of present instrumentation must be addressed before a proteomics profiling platform suitable for efficient clinical applications can be routinely implemented.     

Urinary proteome profiling using microfluidic technology on a chip

Clinical diagnostics and biomarker discovery are the major focuses of current clinical proteomics. In the present study, we applied microfluidic technology on a chip for proteome profiling of human urine from 31 normal healthy individuals (15 males and 16 females), 6 patients with diabetic nephropathy (DN), and 4 patients with IgA nephropathy (IgAN). Using only 4 microL of untreated urine, automated separation of proteins/peptides was achieved, and 1-7 (3.8 +/- 0.3) spectra/bands of urinary proteins/peptides were observed in the normal urine, whereas 8-16 (11.3 +/- 1.2) and 9-14 (10.8 +/- 1.2) spectra were observed in urine samples of DN and IgAN, respectively. Coefficient of variations of amplitudes of lower marker (1.2 kDa), system spectra (6-8 kDa), and upper marker (260.0 kDa) were 22.84, 24.92, and 32.65%, respectively. ANOVA with Tukey post-hoc multiple comparisons revealed 9 spectra of which amplitudes significantly differed between normal and DN urine (DN/normal amplitude ratios ranged from 2.9 to 3102.7). Moreover, the results also showed that 3 spectra (with molecular masses of 12-15, 27-28, and 34-35 kDa) were significantly different between DN and IgAN urine (DN/IgAN amplitude ratios ranged from 3.9 to 7.4). In addition to the spectral amplitudes, frequencies of some spectra could differentiate the normal from the diseased urine but could not distinguish between DN and IgAN. There was no significant difference, regarding the spectral amplitude or frequency, observed between males and females. These data indicate that the microfluidic chip technology is applicable for urinary proteome profiling with potential uses in clinical diagnostics and biomarker discovery.     

Enhanced recovery of lyophilized peptides in shotgun proteomics by using an LC‐ESI‐MS compatible surfactant

LC‐ESI/MS/MS‐based shotgun proteomics is currently the most commonly used approach for the identification and quantification of proteins in large‐scale studies of biomarker discovery. In the past several years, the shotgun proteomics technologies have been refined toward further enhancement of proteome coverage. In the complex series of protocols involved in shotgun proteomics, however, loss of proteolytic peptides during the lyophilization step prior to the LC/MS/MS injection has been relatively neglected despite the fact that the dissolution of the hydrophobic peptides in lyophilized samples is difficult in 0.05–0.1% TFA or formic acid, causing substantial loss of precious peptide samples. In order to prevent the loss of peptide samples during this step, we devised a new protocol using Invitrosol (IVS), a commercially available surfactant compatible with ESI‐MS; by dissolving the lyophilized peptides in IVS, we show improved recovery of hydrophobic peptides, leading to enhanced coverage of proteome. Thus, the use of IVS in the recovery step of lyophilized peptides will help the shotgun proteomics analysis by expanding the proteome coverage, which would significantly promote the discovery and development of new diagnostic markers and therapeutic targets.     

Applications of cell-based phage display panning to proteomic analysis

In the post-genomic era, proteomics together with genomic tools have led to powerful new strategies in basic and clinical research. These combined “omics” technologies are being integrated into the drug target discovery process. Unlike the genome, the proteome is a highly dynamic entity that requires techniques capable of analyzing on selected populations of proteins in specific biological conditions that reflect the proteins’ functional characteristics. Antibodies have become one of the most important reagents for the analysis of selected populations of proteins, and the application of phage-display antibody libraries to high-throughput antibody generation against large numbers of various antigens provides a tool for proteome-wide protein expression analysis. In this review, we will discuss the utility of phage-display antibodies in proteomics applications, specifically for the discovery of novel disease markers and therapeutic targets.     

Characterization of the human urinary proteome: a method for high-resolution display of urinary proteins on two-dimensional electrophoresis gels with a yield of nearly 1400 distinct protein spots

The abundance profile of the human urinary proteome is known to change as a result of diseases or drug toxicities, particularly of those affecting the kidney and the urogenital tract. A consequence of such insults is the ability to identify proteins in urine, which may be useful as quantitative biomarkers. To succeed in discovering them, reproducible urine sample preparation methods and good protein resolution in two-dimensional electrophoresis (2-DE) gels for parallel semiquantitative protein measurements are desirable. Here, we describe a protein fractionation strategy enriching proteins of molecular masses (M(r)) lower than 30 kDa in a fraction separate from larger proteins. The fraction containing proteins with M(r)s higher than 30 kDa was subsequently subjected to immunoaffinity subtraction chromatography removing most of the highly abundant albumin and immunoglobulin G. Following 2-DE display, superior protein spot resolution was observed. Subsequent high-throughput mass spectrometry analysis of ca. 1400 distinct spots using matrix-assisted laser desorption/ionization-time of flight peptide mass fingerprinting and liquid chromatography-electrospray ionization tandem mass spectrometry lead to the successful identification of 30% of the proteins. As expected from high levels of post-translational modifications in most urinary proteins and the presence of proteolytic products, ca. 420 identified spots collapsed into 150 unique protein annotations. Only a third of the proteins identified in this study are described as classical plasma proteins in circulation, which are known to be relatively abundant in urine despite their retention to a large extent in the glomerular blood filtration process. As a proof of principle that our urinary proteome display effort holds promise for biomarker discovery, proteins isolated from the urine of a renal cell carcinoma patient were profiled prior to and after nephrectomy. Particularly, the decrease in abundance of the kininogen 2-DE gel spot train in urine after surgery was striking.     

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.     

Application of Mass Spectrometry in Proteomics

Mass spectrometry has arguably become the core technology in proteomics. The application of mass spectrometry based techniques for the qualitative and quantitative analysis of global proteome samples derived from complex mixtures has had a big impact in the understanding of cellular function. Here, we give a brief introduction to principles of mass spectrometry and instrumentation currently used in proteomics experiments. In addition, recent developments in the application of mass spectrometry in proteomics are summarised. Strategies allowing high-throughput identification of proteins from highly complex mixtures include accurate mass measurement of peptides derived from total proteome digests and multidimensional peptide separations coupled with mass spectrometry. Mass spectrometric analysis of intact proteins permits the characterisation of protein isoforms. Recent developments in stable isotope labelling techniques and chemical tagging allow the mass spectrometry based differential display and quantitation of proteins, and newly established affinity procedures enable the targeted characterisation of post-translationally modified proteins. Finally, advances in mass spectrometric imaging allow the gathering of specific information on the local molecular composition, relative abundance and spatial distribution of peptides and proteins in thin tissue sections.     

Enhanced detection of low abundance human plasma proteins using a tandem IgY12-SuperMix immunoaffinity separation strategy

The enormous dynamic range of human bodily fluid proteomes poses a significant challenge for current MS-based proteomics technologies as it makes it especially difficult to detect low abundance proteins in human biofluids such as blood plasma, which is an essential aspect for successful biomarker discovery efforts. Here we present a novel tandem IgY12-SuperMix immunoaffinity separation system for enhanced detection of low abundance proteins in human plasma. The tandem IgY12-SuperMix system separates approximately 60 abundant proteins from the low abundance proteins in plasma, allowing for significant enrichment of low abundance plasma proteins in the SuperMix flow-through fraction. High reproducibility of the tandem separations was observed in terms of both sample processing recovery and LC-MS/MS identification results based on spectral count data. The ability to quantitatively measure differential protein abundances following application of the tandem separations was demonstrated by spiking six non-human standard proteins at three different levels into plasma. A side-by-side comparison between the SuperMix flow-through and IgY12 flow-through samples analyzed by both one- and two-dimensional LC-MS/MS revealed a 60-80% increase in proteome coverage as a result of the SuperMix separations, suggesting significantly enhanced detection of low abundance proteins. A total of 695 plasma proteins were confidently identified in a single analysis (with a minimum of two peptides per protein) by coupling the tandem separation strategy with two-dimensional LC-MS/MS, including 42 proteins with reported normal concentrations of approximately 100 pg/ml to 100 ng/ml. The concentrations of two selected proteins, macrophage colony-stimulating factor 1 and matrix metalloproteinase-8, were independently validated by ELISA as 202 pg/ml and 12.4 ng/ml, respectively. Evaluation of binding efficiency revealed that 45 medium abundance proteins were efficiently captured by the SuperMix column with >90% retention. Taken together, these results illustrate the potential broad utilities of this tandem IgY12-SuperMix strategy for proteomics applications involving human biofluids where effectively addressing the dynamic range challenge of the specimen is imperative.     

Halobacterium salinarum NRC-1 PeptideAtlas: toward strategies for targeted proteomics and improved proteome coverage

The relatively small numbers of proteins and fewer possible post-translational modifications in microbes provide a unique opportunity to comprehensively characterize their dynamic proteomes. We have constructed a PeptideAtlas (PA) covering 62.7% of the predicted proteome of the extremely halophilic archaeon Halobacterium salinarum NRC-1 by compiling approximately 636 000 tandem mass spectra from 497 mass spectrometry runs in 88 experiments. Analysis of the PA with respect to biophysical properties of constituent peptides, functional properties of parent proteins of detected peptides, and performance of different mass spectrometry approaches has highlighted plausible strategies for improving proteome coverage and selecting signature peptides for targeted proteomics. Notably, discovery of a significant correlation between absolute abundances of mRNAs and proteins has helped identify low abundance of proteins as the major limitation in peptide detection. Furthermore, we have discovered that iTRAQ labeling for quantitative proteomic analysis introduces a significant bias in peptide detection by mass spectrometry. Therefore, despite identifying at least one proteotypic peptide for almost all proteins in the PA, a context-dependent selection of proteotypic peptides appears to be the most effective approach for targeted proteomics.     

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.     

A high-confidence human plasma proteome reference set with estimated concentrations in PeptideAtlas

Human blood plasma can be obtained relatively noninvasively and contains proteins from most, if not all, tissues of the body. Therefore, an extensive, quantitative catalog of plasma proteins is an important starting point for the discovery of disease biomarkers. In 2005, we showed that different proteomics measurements using different sample preparation and analysis techniques identify significantly different sets of proteins, and that a comprehensive plasma proteome can be compiled only by combining data from many different experiments. Applying advanced computational methods developed for the analysis and integration of very large and diverse data sets generated by tandem MS measurements of tryptic peptides, we have now compiled a high-confidence human plasma proteome reference set with well over twice the identified proteins of previous high-confidence sets. It includes a hierarchy of protein identifications at different levels of redundancy following a clearly defined scheme, which we propose as a standard that can be applied to any proteomics data set to facilitate cross-proteome analyses. Further, to aid in development of blood-based diagnostics using techniques such as selected reaction monitoring, we provide a rough estimate of protein concentrations using spectral counting. We identified 20,433 distinct peptides, from which we inferred a highly nonredundant set of 1929 protein sequences at a false discovery rate of 1%. We have made this resource available via PeptideAtlas, a large, multiorganism, publicly accessible compendium of peptides identified in tandem MS experiments conducted by laboratories around the world.     

Improvements in proteomic metrics of low abundance proteins through proteome equalization using ProteoMiner prior to MudPIT

Ideally, shotgun proteomics would facilitate the identification of an entire proteome with 100% protein sequence coverage. In reality, the large dynamic range and complexity of cellular proteomes results in oversampling of abundant proteins, while peptides from low abundance proteins are undersampled or remain undetected. We tested the proteome equalization technology, ProteoMiner, in conjunction with Multidimensional Protein Identification Technology (MudPIT) to determine how the equalization of protein dynamic range could improve shotgun proteomics methods for the analysis of cellular proteomes. Our results suggest low abundance protein identifications were improved by two mechanisms: (1) depletion of high abundance proteins freed ion trap sampling space usually occupied by high abundance peptides and (2) enrichment of low abundance proteins increased the probability of sampling their corresponding more abundant peptides. Both mechanisms also contributed to dramatic increases in the quantity of peptides identified and the quality of MS/MS spectra acquired due to increases in precursor intensity of peptides from low abundance proteins. From our large data set of identified proteins, we categorized the dominant physicochemical factors that facilitate proteome equalization with a hexapeptide library. These results illustrate that equalization of the dynamic range of the cellular proteome is a promising methodology to improve low abundance protein identification confidence, reproducibility, and sequence coverage in shotgun proteomics experiments, opening a new avenue of research for improving proteome coverage.     

Zooming in: fractionation strategies in proteomics

The recent development of mass spectrometry, i.e., high sensitivity, automation of protein identification and some post-translational modifications (PTMs) significantly increased the number of large-scale proteomics projects. However, there are still considerable limitations as none of the currently available proteomics techniques allows the analysis of an entire proteome in a single step procedure. On the other hand, there are several successful studies analyzing well defined groups of proteins, e.g., proteins of purified organelles, membrane microdomains or isolated proteins with certain PTMs. Coupling of advanced separation methodologies (different prefractionation strategies, such as subcellular fractionation, affinity purification, fractionation of proteins and peptides according to their physicochemical properties) to highly sensitive mass spectrometers provides powerful means to detect and analyze dynamic changes of low abundant regulatory proteins in eukaryotic cells on the subcellular level. This review summarizes and discusses recent strategies in proteomics approaches where different fractionation strategies were successfully applied.     

Chromatographic isolation of methionine-containing peptides for gel-free proteome analysis: identification of more than 800 Escherichia coli proteins

A novel gel-free proteomic technology was used to identify more than 800 proteins from 50 million Escherichia coli K12 cells in a single analysis. A peptide mixture is first obtained from a total unfractionated cell lysate, and only the methionine-containing peptides are isolated and identified by mass spectrometry and database searching. The sorting procedure is based on the concept of diagonal chromatography but adapted for highly complex mixtures. Statistical analysis predicts that we have identified more than 40% of the expressed proteome, including soluble and membrane-bound proteins. Next to highly abundant proteins, we also detected low copy number components such as the E. coli lactose operon repressor, illustrating the high dynamic range. The method is about 100 times more sensitive than two-dimensional gel-based methods and is fully automated. The strongest point, however, is the flexibility in the peptide sorting chemistry, which may target the technique toward quantitative proteomics of virtually every class of peptides containing modifiable amino acids, such as phosphopeptides, amino-terminal peptides, etc., adding a new dimension to future proteome research.     

2D-electrophoresis and the urine proteome map: Where do we stand?

The discovery of urinary biomarkers is a main topic in clinical medicine. The development of proteomics has rapidly changed the knowledge on urine protein composition and probably will modify it again. Two-dimensional electrophoresis (2D-PAGE) coupled with mass spectrometry has represented for years the technique of choice for the analysis of urine proteins and it is time to draw some conclusions.This review will focus on major methodological aspects related to urine sample collection, storage and analysis by 2D-PAGE and attempt to define an advanced normal urine protein map.Overall, 1118 spots were reproducibly found in normal urine samples but only 275 were characterized as isoforms of 82 proteins. One-hundred height spots belonging to 30 proteins were also detected in plasma and corresponded to typical plasma components. The identity of most of the proteins found in normal urine by 2D-PAGE remains to be determined, the majority being low-molecular weight proteins (< 30 kDa). Equalization procedures would also enhance sensitivity of the analysis and allow low abundance proteins to be characterized.Therefore, we are still on the way to define the normal urine composition. Technology advancements in concentrating procedure will improve sensitivity and give the possibility to purify proteins for mass spectrometry.     

High throughput proteome screening for biomarker detection

Mass spectrometry-based quantitative proteomics has become an important component of biological and clinical research. Current methods, while highly developed and powerful, are falling short of their goal of routinely analyzing whole proteomes mainly because the wealth of proteomic information accumulated from prior studies is not used for the planning or interpretation of present experiments. The consequence of this situation is that in every proteomic experiment the proteome is rediscovered. In this report we describe an approach for quantitative proteomics that builds on the extensive prior knowledge of proteomes and a platform for the implementation of the method. The method is based on the selection and chemical synthesis of isotopically labeled reference peptides that uniquely identify a particular protein and the addition of a panel of such peptides to the sample mixture consisting of tryptic peptides from the proteome in question. The platform consists of a peptide separation module for the generation of ordered peptide arrays from the combined peptide sample on the sample plate of a MALDI mass spectrometer, a high throughput MALDI-TOF/TOF mass spectrometer, and a suite of software tools for the selective analysis of the targeted peptides and the interpretation of the results. Applying the method to the analysis of the human blood serum proteome we demonstrate the feasibility of using mass spectrometry-based proteomics as a high throughput screening technology for the detection and quantification of targeted proteins in a complex system.