Biomarker discovery in urine by proteomics

Urinary biomarkers in diabetic nephropathy

Diabetic nephropathy (DN), a significant consequence of diabetes, is associated with adverse cardiovascular and renal disease as well as mortality. Although microalbuminuria is considered the best non-invasive marker for DN, better predictive markers are needed of sufficient sensitivity and specificity to detect disease in general and in early disease specifically. Even prior to appearance of microalbuminuria, urinary biomarkers increase in diabetics and can serve as accurate nephropathy biomarkers even in normoalbuminuria. In this review, a number of novel urine biomarkers including those reflecting kidney damage caused by glomerular/podocyte damage, tubular damage, oxidative stress, inflammation, and intrarenal renin-angiotensin system activation are discussed. Our review also includes emerging biomarkers such as urinary microRNAs. These short noncoding miRNAs regulate gene expression and could be utilized to identify potential novel biomarkers in DN development and progression. .

Isocitrate dehydrogenase 1 upregulation in urinary extracellular vesicles from proximal tubules of type 2 diabetic rats

Diabetic nephropathy (DN) is a major cause of chronic kidney disease. Microalbuminuria is currently the most common non-invasive biomarker for the early diagnosis of DN. However, renal structural damage may have advanced when albuminuria is detected. In this study, we sought biomarkers for early DN diagnosis through proteomic analysis of urinary extracellular vesicles (uEVs) from type 2 diabetic model rats and normal controls. Isocitrate dehydrogenase 1 (IDH1) was significantly increased in uEVs from diabetic model rats at the early stage despite minimal differences in albuminuria between the groups. Calorie restriction significantly suppressed the increase in IDH1 in uEVs and 24-hour urinary albumin excretion, suggesting that the increase in IDH1 in uEVs was associated with the progression of DN. Additionally, we investigated the origin of IDH1-containing uEVs based on their surface sugar chains. Lectin affinity enrichment and immunohistochemical staining showed that IDH1-containing uEVs were derived from proximal tubules. These findings suggest that the increase in IDH1 in uEVs reflects pathophysiological alterations in the proximal tubules and that IDH1 in uEVs may serve as a potential biomarker of DN in the proximal tubules.

A Standardized Protocol for Assuring the Validity of Proteomics Results from Liquid Chromatography-High-Resolution Mass Spectrometry

Significant advances in the technological development of mass spectrometry in the field of proteomics and the generation of extremely large amounts of data require a very critical approach to assure the validity of results. Commonly used procedures involved liquid chromatography followed by high-resolution mass spectrometry measurements. Proteomics analysis is used in many fields including the investigation of the metabolism of biologically active substances in organisms. Thus, there is a need to care about the validity of the obtained results. In this work, we proposed a standardized protocol for proteomic analysis using liquid chromatography-high-resolution mass spectrometry, which covers all of these analytical steps to ensure the validity of the results. For this purpose, we explored the requirements of the ISO/IEC 17025:2017 standard as a reference document for quality control in biochemistry research-based mass spectrometry.

Effects of Chlorpyrifos on Serine Hydrolase Activities, Lipid Mediators, and Immune Responses in Lungs of Neonatal and Adult Mice

Chlorpyrifos (CPF) is an organophosphate (OP) pesticide that causes acute toxicity by inhibiting acetylcholinesterase (AChE) in the nervous system. However, endocannabinoid (eCB) metabolizing enzymes in brain of neonatal rats are more sensitive than AChE to inhibition by CPF, leading to increased levels of eCBs. Because eCBs are immunomodulatory molecules, we investigated the association between eCB metabolism, lipid mediators, and immune function in adult and neonatal mice exposed to CPF. We focused on lung effects because epidemiologic studies have linked pesticide exposures to respiratory diseases. CPF was hypothesized to disrupt lung eCB metabolism and alter lung immune responses to lipopolysaccharide (LPS), and these effects would be more pronounced in neonatal mice due to an immature immune system. We first assessed the biochemical effects of CPF in adult mice (≥8 weeks old) and neonatal mice after administering CPF (2.5 mg/kg, oral) or vehicle for 7 days. Tissues were harvested 4 h after the last CPF treatment and lung microsomes from both age groups demonstrated CPF-dependent inhibition of carboxylesterases (Ces), a family of xenobiotic and lipid metabolizing enzymes, whereas AChE activity was inhibited in adult lungs only. Activity-based protein profiling (ABPP)-mass spectrometry of lung microsomes identified 31 and 32 individual serine hydrolases in neonatal lung and adult lung, respectively. Of these, Ces1c/Ces1d/Ces1b isoforms were partially inactivated by CPF in neonatal lung, whereas Ces1c/Ces1b and Ces1c/BChE were partially inactivated in adult female and male lungs, respectively, suggesting age- and sex-related differences in their sensitivity to CPF. Monoacylglycerol lipase (MAGL) and fatty acid amide hydrolase (FAAH) activities in lung were unaffected by CPF. When LPS (1.25 mg/kg, i.p.) was administered following the 7-day CPF dosing period, little to no differences in lung immune responses (cytokines and immunophenotyping) were noted between the CPF and vehicle groups. However, a CPF-dependent increase in the amounts of dendritic cells and certain lipid mediators in female lung following LPS challenge was observed. Experiments in neonatal and adult Ces1d^-/- mice yielded similar results as wild type mice (WT) following CPF treatment, except that CPF augmented LPS-induced Tnfa mRNA in adult Ces1d^-/- mouse lungs. This effect was associated with decreased expression of Ces1c mRNA in Ces1d^-/- mice versus WT mice in the setting of LPS exposure. We conclude that CPF exposure inactivates several Ces isoforms in mouse lung and, during an inflammatory response, increases certain lipid mediators in a female-dependent manner. However, it did not cause widespread altered lung immune effects in response to an LPS challenge.

Gold nanoparticles-based assays for biodetection in urine

Urine is a biofluid easy to collect through a non-invasive technique that allows collecting a large volume of sample. The use of urine for disease diagnosis is not yet well explored. However, it has gained attention over the last three years. It has been applied in the diagnosis of several illnesses such as kidney disease, bladder cancer, prostate cancer and cardiovascular diseases. In the last decade, gold nanoparticles (Au NPs) have attracted attention in biosensors' development for the diagnosis of diseases due to their electrical and optical properties, ability to conjugate with biomolecules, high sensitivity, and selectivity. Therefore, this article aims to present a comprehensive view of state of the art on the advances made in the quantification of analytes in urinary samples using AuNPs based assays, with a focus on protein analysis. The type of diagnosis methods, the Au NPs synthesis approaches and the strategies for surface modification aiming at selectivity towards the different targets are highlighted.

Human prorenin determination by hybrid immunocapture liquid chromatography/mass spectrometry: A mixed-solvent-triggered digestion utilizing D-optimal design

RATIONALE

Human prorenin, representing the precursor of mature renin, has been discussed as a potential biomarker, e.g. in diagnosing primary hyperaldosteronism or diabetes-induced nephropathy. Currently, only immunoassays are available for prorenin quantification. As the similarity of prorenin to active renin impedes its accurate determination by immunoassay, mass spectrometry appears as an accurate alternative for differentiation of that protein.

METHODS

Immunoaffinity purification plus a mixed-solvent-triggered digestion was combined with liquid chromatography/mass spectrometry (LC/MS) to enable a fast, sensitive, and less laboratory-intensive approach to the quantification of prorenin. Statistical experimental planning, which is known as Design of Experiments (DOE), was used to identify the optimal conditions for the generation of the signature peptides within a manageable number of experiments. The efficiency of the mixed-solvent-triggered digestion by trypsin was investigated using four different organic solvents: acetonitrile, acetone, tetrahydrofuran and methanol.

RESULTS

By utilizing a D-optimal design, we found that the optimal mixed-solvent type for the generation of both signature peptides was acetonitrile at a concentration of 84% and an incubation temperature of 16°C. Using the mixed-solvent-triggered digestion, the procedure time allowed a fast analysis of active renin and prorenin with a short digestion time of 98 min. This optimized mixed-solvent-triggered digestion procedure was applied to detect renin and prorenin successfully in human plasma by the newly developed hybrid approach.

CONCLUSIONS

The identification of unique surrogates for human prorenin enabled the mass spectrometric differentiation between the two similar proteins. The novel hybrid approach successfully proved its ability to purify, detect and distinguish between prorenin and active renin in human plasma.

Mapping human N-linked glycoproteins and glycosylation sites using mass spectrometry

N-linked glycoprotein is a highly interesting class of proteins for clinical and biological research. Over the last decade, large-scale profiling of N-linked glycoproteins and glycosylation sites from biological and clinical samples has been achieved through mass spectrometry-based glycoproteomic approaches. In this paper, we reviewed the human glycoproteomic profiles that have been reported in more than 80 individual studies, and mainly focused on the N-glycoproteins and glycosylation sites identified through their deglycosylated forms of glycosite-containing peptides. According to our analyses, more than 30,000 glycosite-containing peptides and 7,000 human glycoproteins have been identified from five different body fluids, twelve human tissues (or related cell lines), and four special cell types. As the glycoproteomic data is still missing for many organs and tissues, a systematical glycoproteomic analysis of various human tissues and body fluids using a uniform platform is still needed for an integrated map of human N-glycoproteomes.

Urine Biomarkers for the Early Detection of Ovarian Cancer - Are We There Yet?

Ovarian cancer affects around 7500 women in the United Kingdom every year. Despite this, there is no effective screening strategy or standard treatment for ovarian cancer. If diagnosed during stage I, ovarian cancer has a 90% 5-year survival rate; however, there is usually a masking of symptoms which leads to an often late-stage diagnosis and correspondingly poor survival rate. Current diagnostic methods are invasive and consist of a pelvic examination, transvaginal ultrasonography, and blood tests to detect cancer antigen 125 (CA125). Unfortunately, surgery is often still required to make a positive diagnosis. To address the need for accurate, specific, and non-invasive diagnostic methods, there has been an increased interest in biomarkers identified through non-invasive tests as tools for the earlier diagnosis of ovarian cancer. Although most studies have focused on the identification of biomarkers in blood, the ease of availability of urine and the high patient compliance rates suggest that it could provide a promising resource for the screening of patients for ovarian cancer.

Methodology and Applications of Disease Biomarker Identification in Human Serum

Biomarkers are biomolecules that serve as indicators of biological and pathological processes, or physiological and pharmacological responses to a drug treatment. Because of the high abundance of albumin and heterogeneity of plasma lipoproteins and glycoproteins, biomarkers are difficult to identify in human serum. Due to the clinical significance the identification of disease biomarkers in serum holds great promise for personalized medicine, especially for disease diagnosis and prognosis. This review summarizes some common and emerging proteomics techniques utilized in the separation of serum samples and identification of disease signatures. The practical application of each protein separation or identification technique is analyzed using specific examples. Biomarkers of cancers of prostate, breast, ovary, and lung in human serum have been reviewed, as well as those of heart disease, arthritis, asthma, and cystic fibrosis. Despite the advancement of technology few biomarkers have been approved by the Food and Drug Administration for disease diagnosis and prognosis due to the complexity of structure and function of protein biomarkers and lack of high sensitivity, specificity, and reproducibility for those putative biomarkers. The combination of different types of technologies and statistical analysis may provide more effective methods to identify and validate new disease biomarkers in blood.

Detection of aggressive prostate cancer associated glycoproteins in urine using glycoproteomics and mass spectrometry

Clinical management of prostate cancer remains a significant challenge due to the lack of available tests for guiding treatment decisions. The blood prostate-specific antigen test has facilitated early detection and intervention of prostate cancer. However, blood prostate-specific antigen levels are less effective in distinguishing aggressive from indolent prostate cancers and other benign prostatic diseases. Thus, the development of novel approaches specific for prostate cancer that can differentiate aggressive from indolent disease remains an urgent medical need. In the current study, we evaluated urine specimens from prostate cancer patients using LC-MS/MS, with the aim of identifying effective urinary prostate cancer biomarkers. Glycoproteins from urine samples of prostate cancer patients with different Gleason scores were characterized via solid phase extraction of N-linked glycosite-containing peptides and LC-MS/MS. A total of 2923 unique glycosite-containing peptides were identified. Glycoproteomic comparison on urine and tissues from aggressive and non-aggressive prostate cancers as well as sera from prostate cancer patients revealed that the majority of AG prostate cancer associated glycoproteins were more readily detected in patient's urine than serum samples. Our data collectively indicate that urine provides a potential source for biomarker testing in patients with AG prostate cancer.

Thousand and one ways to quantify and compare protein abundances in label-free bottom-up proteomics

How to process and analyze MS data to quantify and statistically compare protein abundances in bottom-up proteomics has been an open debate for nearly fifteen years. Two main approaches are generally used: the first is based on spectral data generated during the process of identification (e.g. peptide counting, spectral counting), while the second makes use of extracted ion currents to quantify chromatographic peaks and infer protein abundances based on peptide quantification. These two approaches actually refer to multiple methods which have been developed during the last decade, but were submitted to deep evaluations only recently. In this paper, we compiled these different methods as exhaustively as possible. We also summarized the way they address the different problems raised by bottom-up protein quantification such as normalization, the presence of shared peptides, unequal peptide measurability and missing data. This article is part of a Special Issue entitled: Plant Proteomics--a bridge between fundamental processes and crop production, edited by Dr. Hans-Peter Mock.

State-of-the-art nanoplatform-integrated MALDI-MS impacting resolutions in urinary proteomics

Urine proteomics has become a subject of interest, since it has led to a number of breakthroughs in disease diagnostics. Urine contains information not only from the kidney and the urinary tract but also from other organs, thus urinary proteome analysis allows for identification of biomarkers for both urogenital and systemic diseases. The following review gives a brief overview of the analytical techniques that have been in practice for urinary proteomics. MALDI-MS technique and its current application status in this area of clinical research have been discussed. The review comments on the challenges facing the conventional MALDI-MS technique and the upgradation of this technique with the introduction of nanotechnology. This review projects nano-based techniques such as nano-MALDI-MS, surface-assisted laser desorption/ionization, and nanostructure-initiator MS as the platforms that have the potential in trafficking MALDI-MS from the lab to the bedside.

Microscale depletion of high abundance proteins in human biofluids using IgY14 immunoaffinity resin: analysis of human plasma and cerebrospinal fluid

Removal of highly abundant proteins in plasma is often carried out using immunoaffinity depletion to extend the dynamic range of measurements to lower abundance species. While commercial depletion columns are available for this purpose, they generally are not applicable to limited sample quantities (<20 μL) due to low yields stemming from losses caused by nonspecific binding to the column matrix and concentration of large eluent volumes. Additionally, the cost of the depletion media can be prohibitive for larger-scale studies. Modern LC-MS instrumentation provides the sensitivity necessary to scale-down depletion methods with minimal sacrifice to proteome coverage, which makes smaller volume depletion columns desirable for maximizing sample recovery when samples are limited, as well as for reducing the expense of large-scale studies. We characterized the performance of a 346 μL column volume microscale depletion system, using four different flow rates to determine the most effective depletion conditions for ∼6-μL injections of human plasma proteins and then evaluated depletion reproducibility at the optimum flow rate condition. Depletion of plasma using a commercial 10-mL depletion column served as the control. Results showed depletion efficiency of the microscale column increased as flow rate decreased, and that our microdepletion was reproducible. In an initial application, a 600-μL sample of human cerebrospinal fluid (CSF) pooled from multiple sclerosis patients was depleted and then analyzed using reversed phase liquid chromatography-mass spectrometry to demonstrate the utility of the system for this important biofluid where sample quantities are more commonly limited.

Targeted proteomics using immunoblotting technique for studying dysregulation of ion transporters in renal disorders

Renal salt and water transport physiology has benefited tremendously from the rapid advance of proteomics. Proteomics developed as a fast-throughput means of screening for global changes in proteins in a selected tissue, organ or cell type, as a logical offshoot of similar comprehensive, messenger RNA array-type technology. Targeted proteomics utilizes similar techniques but examines a predetermined set of proteins. One approach that has been rigorously employed over the last 10 years to evaluate differences in renal protein abundances due to a treatment or genotype has been parallel semiquantitative immunoblotting using antibody arrays. This approach, and newer ones on the horizon, provide a rapid global overview of regulation of the individual proteins whose integrated action determines overall renal sodium or water reabsorption.

Distributed computing and data storage in proteomics: many hands make light work, and a stronger memory

Modern day proteomics generates ever more complex data, causing the requirements on the storage and processing of such data to outgrow the capacity of most desktop computers. To cope with the increased computational demands, distributed architectures have gained substantial popularity in the recent years. In this review, we provide an overview of the current techniques for distributed computing, along with examples of how the techniques are currently being employed in the field of proteomics. We thus underline the benefits of distributed computing in proteomics, while also pointing out the potential issues and pitfalls involved.

Autocrine GM-CSF transcription in the leukemic progenitor cell line KG1a is mediated by the transcription factor ETS1 and is negatively regulated through SECTM1 mediated ligation of CD7

BACKGROUND

CD7 expression is found on ~30% of acute myeloblastic leukemias (AML). The leukemic progenitor cell line KG1a (CD7+) constitutively expresses GM-CSF while the parental KG1 (CD7-) cell line does not. This study focuses on the molecular basis of CD7 mediated GM-CSF regulation.

METHODS

KG1a cells were treated with recombinant SECTM1-Fc protein, the PI3K kinase inhibitors wortmannin, LY292004, or PI4K activator spermine. Stable KG1-CD7+, KG1a-shCD7, KG1a-shETS1 as well as KG1a-GFP, KG1a-PKCβII-GFP cell lines were generated and the levels of CD7, GM-CSF and ETS-1 mRNA and protein were compared by real-time-PCR, western blotting, flow cytometry and ELISA.

RESULTS

SECTM1 is expressed in Human Bone Marrow Endothelial Cells (HBMEC) and its expression can be upregulated by both IFN-γ. KG1a cells demonstrated high expression levels of CD7 and ETS-1 allowing a constitutative signaling through the PI3K/Atk pathway to promote GM-CSF expression, while KG1 cells with low expression of CD7 and ETS-1 showed low GM-CSF expression. On KG1a cells GM-CSF expression could be negatively regulated by PI3K inhibitors or by recombinant SECTM1-Fc. Overexpression of CD7 in KG1 cells was insufficient to promote GM-CSF expression, while silencing of CD7 or ETS-1 resulted in reduced GM-CSF expression levels. Differentiation capable KG1a cells overexpressing PKCβII illustrated complete loss of CD7, but maintained normal levels of both ETS-1 and GM-CSF expression.

CONCLUSION

These findings add an additional layer to the previously described autocrine/paracrine signaling between leukemic progenitor cells and the bone marrow microenvironment and highlight a role for SECTM1 in both normal and malignant hematopoiesis.

GENERAL SIGNIFICANCE

This work shows that SECTM1 secreted from bone marrow stromal cells may interact with CD7 to influence GM-CSF expression in leukemic cells.

Application of machine learning to proteomics data: classification and biomarker identification in postgenomics biology

Mass spectrometry is an analytical technique for the characterization of biological samples and is increasingly used in omics studies because of its targeted, nontargeted, and high throughput abilities. However, due to the large datasets generated, it requires informatics approaches such as machine learning techniques to analyze and interpret relevant data. Machine learning can be applied to MS-derived proteomics data in two ways. First, directly to mass spectral peaks and second, to proteins identified by sequence database searching, although relative protein quantification is required for the latter. Machine learning has been applied to mass spectrometry data from different biological disciplines, particularly for various cancers. The aims of such investigations have been to identify biomarkers and to aid in diagnosis, prognosis, and treatment of specific diseases. This review describes how machine learning has been applied to proteomics tandem mass spectrometry data. This includes how it can be used to identify proteins suitable for use as biomarkers of disease and for classification of samples into disease or treatment groups, which may be applicable for diagnostics. It also includes the challenges faced by such investigations, such as prediction of proteins present, protein quantification, planning for the use of machine learning, and small sample sizes.

Tailoring of a TiO2 nanotube array-integrated portable microdevice for efficient on-chip enrichment and isotope labeling of serum phosphopeptides

Herein we present a gravity-driven microdevice furnished with tunable TiO2 nanotube arrays (TNAs) inside as the separation medium for consecutive on-chip enrichment and isotope labeling of serum phosphopeptides. The 3D tubular architectures of TNAs dramatically enhanced the affinity towards phosphate-containing molecules and also provided a spacious microenvironment for isotope dimethyl labeling reactions. To maximize the efficiency and capacity of the phosphopeptide enrichment, nanoscale tailoring and microscale fabrication were employed for adjusting the TNAs' pore sizes and the channel patterns. The S-shaped microdevice equipped with interior TNAs anodized at 25 V was utilised for consecutive serum processing, and further differential expression analysis of endogenous phosphopeptides between ovarian cancer patients and healthy women. The phosphorylated fibrinogen peptide A (FPA, AD[pS]GEGDFLAEGGGVR) was found to be down-regulated by about 4 times while its isoform (D[pS]GEGDFLAEGGGV) was 2.4-fold up-regulated in the patient specimens. In principle, this nanostructure-embedded model introduced tailor-made bioseparation materials into the microdevice, undoubtedly facilitating the workflow of sample pretreatment and thus assisting the analysis of disease-associated biomolecules in biomedical research.

CIINE Reflects Collagenase-Specific CII Breakdown in Cartilage Explant and Whole Body of Canine

To evaluate collagenase inhibitors for the treatment of osteoarthritis and to correlate them with clinical pathology, canine cartilage explant and anterior cruciate ligament transection (ACLT) models were examined by quantifying the CII neoepitope (CIINE). This peptide is a putative marker for collagenase-specific type II collagen (CII) degradation, which is a critical step in osteoarthritis pathology.

The concentration of CIINE in supernatants of canine cartilage explants showed increase upon IL-1β—stimulation and collagenase inhibitors suppressed this elevation of CIINE. In the canine ACLT model, levels of CIINE in urine (uCIINE) increased as lesions of knee joint cartilage developed and decreased in response to collagenase inhibitors.

Our results suggest that CIINE reflects collagenase-specific CII degradation in canine explants and whole bodies. It is anticipated that these data will establish a tool for clarifying and bridging the efficacy and mechanism of collagenase inhibitors at the preclinical stage of drug discovery.

Use of proteomic methods in the analysis of human body fluids in Alzheimer research

Proteomics is the study of the entire population of proteins and peptides in an organism or a part of it, such as a cell, tissue, or fluids like cerebrospinal fluid, plasma, serum, urine, or saliva. It is widely assumed that changes in the composition of the proteome may reflect disease states and provide clues to its origin, eventually leading to targets for new treatments. The ability to perform large-scale proteomic studies now is based jointly on recent advances in our analytical methods. Separation techniques like CE and 2DE have developed and matured. Detection methods like MS have also improved greatly in the last 5 years. These developments have also driven the fields of bioinformatics, needed to deal with the increased data production and systems biology. All these developing methods offer specific advantages but also come with certain limitations. This review describes the different proteomic methods used in the field, their limitations, and their possible pitfalls. Based on a literature search in PubMed, we identified 112 studies that applied proteomic techniques to identify biomarkers for Alzheimer disease. This review describes the results of these studies on proteome changes in human body fluids of Alzheimer patients reviewing the most important studies. We extracted a list of 366 proteins and peptides that were identified by these studies as potential targets in Alzheimer research.

Poor histological lesions in IgA nephropathy may be reflected in blood and urine peptide profiling

Background

IgA nephropathy (IgAN) is the most common primary glomerulonephritis worldwide, leading to renal failure in 15% to 40% of cases. IgAN is diagnosed by renal biopsy, an invasive method that is not risk-free. We used blood and urine peptide profiles as a noninvasive method of linking IgAN-associated changes with histological lesions by Oxford classification.

Methods

We prospectively studied 19 patients with biopsy-proven IgAN and 14 healthy subjects from 2006 to 2009, excluding subjects with crescentic glomerulonephritis and collecting clinical and biochemical data at the time of diagnosis and during follow-up (24 months). Histological lesions were evaluated by Oxford classification. Proteomic analysis was performed by combining magnetic bead (MB) technology and mass spectrometry (MALDI-TOF MS) to obtain peptide profiles. Doubling of serum creatinine was considered a variable of poor renal prognosis.

Results

We identified 55 peptides—13 in serum, 26 in plasma, and 16 in urine—that differentiated IgAN patients from healthy subjects. A significant association was noted between serum/plasma and urine peptides and histological findings—ie, tubulointerstitial damage, segmental glomerulosclerosis, and endocapillary injury.

We also identified 3 peptides—corresponding to bradykinin, uromodulin, and alpha-1-antitrypsin—that were associated with severity of lesions, such as tubulointerstitial damage and segmental glomerulosclerosis.

Moreover, blood peptides with m/z 2953, 5337, 9287, and 9289 and urine peptides with m/z 1769, 1898, 1913, 1945, 2491, 2756, 2977, 3004, 3389, and 4752 correlated significantly with poor renal function.

Conclusions

In patients with IgAN, the use of noninvasive approaches, such as blood and urine proteomics, can provide valuable information beyond that of standard diagnostic techniques, allowing us to identify blood and urine peptide profiles that are associated with poor histological lesions in IgAN patients.

Inactivation of the enzyme GSK3α by the kinase IKKi promotes AKT-mTOR signaling pathway that mediates interleukin-1-induced Th17 cell maintenance

Interleukin-1 (IL-1)-induced activation of the mTOR kinase pathway has major influences on Th17 cell survival, proliferation, and effector function. Via biochemical and genetic approaches, the kinases IKKi and GSK3α were identified as the critical intermediate signaling components for IL-1-induced AKT activation, which in turn activated mTOR. Although insulin-induced AKT activation is known to phosphorylate and inactivate GSK3α and GSK3β, we found that GSK3α but not GSK3β formed a constitutive complex to phosphorylate and suppress AKT activation, showing that a reverse action from GSK to AKT can take place. Upon IL-1 stimulation, IKKi was activated to mediate GSK3α phosphorylation at S21, thereby inactivating GSK3α to promote IL-1-induced AKT-mTOR activation. Thus, IKKi has a critical role in Th17 cell maintenance and/or proliferation through the GSK-AKT-mTOR pathway, implicating the potential of IKKi as a therapeutic target.

Comparing the efficiencies of hydrazide labels in the study of protein carbonylation in human serum albumin

In this work, we establish a methodology for comparing the efficiencies of different hydrazide labels for detecting protein carbonyls. We have chosen acrolein-modified human serum albumin as a model. This system provides a convenient means of reproducibly generating carbonylated protein. Five hydrazide-based labels were tested. Three carry a biotin affinity tag, and the others are simple fatty acid hydrazides. For the biotin-based labels, the yield of the labeling reaction varies considerably, and the most commonly used label, biotin hydrazide, gives the lowest yield. The total tandem mass spectrometry (MS/MS) spectrum counts of modified peptides are similar for all of the biotin-based tags, indicating that factors beyond the labeling efficiency are important in determining the effectiveness of the label. In addition, there is a large variation in the number of spectra obtained for specific, modified peptides depending on the nature of the labeling group. This variation implies that the relative detectability of a particular modification site is highly dependent on the tagging reagent, and more importantly, titration schemes aimed at identifying the most reactive site based on its threshold concentration will be biased by the choice of tagging reagent. The fatty acid hydrazides are somewhat more effective than the biotin-based hydrazides in generating identifiable MS/MS spectra but offer no opportunity for enrichment. For the biotin-based tags, avidin affinity chromatography was used with the tryptic digests, and each tag led to similar enrichment levels.

Uromodulin and α(1)-antitrypsin urinary peptide analysis to differentiate glomerular kidney diseases

BACKGROUND/AIMS

Glomerular kidney disease (GKD) is suspected in patients based on proteinuria, but its diagnosis relies primarily on renal biopsy. We used urine peptide profiling as a noninvasive means to link GKD-associated changes to each glomerular entity.

METHODS

Urinary peptide profiles of 60 biopsy-proven glomerular patients and 14 controls were analyzed by combining magnetic bead peptide enrichment, MALDI-TOF MS analysis, and ClinProTools v2.0 to select differential peptides. Tentative identification of the differential peptides was carried out by HPLC-MS/MS.

RESULTS

The HPLC-MS/MS results suggest that uromodulin (UMOD; m/z: 1682, 1898 and 1913) and α(1)-antitrypsin (A1AT; m/z: 1945, 2392 and 2505) are differentially expressed urinary peptides that distinguish between GKD patients and healthy subjects. Low UMOD and high A1AT peptide abundance was observed in 80-92% of patients with GKD. Proliferative forms of GKD were distinguished from nonproliferative forms, based on a combination of UMOD and A1AT peptides. Nonproliferative forms correlated with higher A1AT peptide levels - focal segmental glomerulosclerosis was linked more closely to high levels of the m/z 1945 peptide than minimal change disease.

CONCLUSION

We describe a workflow - urinary peptide profiling coupled with histological findings - that can be used to distinguish GKD accurately and noninvasively, particularly its nonproliferative forms.

Release of tissue-specific proteins into coronary perfusate as a model for biomarker discovery in myocardial ischemia/reperfusion injury

Diagnosis of acute coronary syndromes is based on protein biomarkers, such as the cardiac troponins (cTnI/cTnT) and creatine kinase (CK-MB) that are released into the circulation. Biomarker discovery is focused on identifying very low abundance tissue-derived analytes from within albumin-rich plasma, in which the wide dynamic range of the native protein complement hinders classical proteomic investigations. We employed an ex vivo rabbit model of myocardial ischemia/reperfusion (I/R) injury using Langendorff buffer perfusion. Nonrecirculating perfusate was collected over a temporal profile of 60 min reperfusion following brief, reversible ischemia (15 min; 15I/60R) for comparison with irreversible I/R (60I/60R). Perfusate proteins were separated using two-dimensional gel electrophoresis (2-DE) and identified by mass spectrometry (MS), revealing 26 tissue-specific proteins released during reperfusion post-15I. Proteins released during irreversible I/R (60I/60R) were profiled using gel-based (2-DE and one-dimensional gel electrophoresis coupled to liquid chromatography and tandem mass spectrometry; geLC-MS) and gel-free (LC-MS/MS) methods. A total of 192 tissue-specific proteins were identified during reperfusion post-60I. Identified proteins included those previously associated with I/R (myoglobin, CK-MB, cTnI, and cTnT), in addition to examples currently under investigation in large cohort studies (heart-type fatty acid binding protein; FABPH). The postischemic release profile of a novel cardiac-specific protein, cysteine and glycine-rich protein 3 (Csrp3; cardiac LIM domain protein) was validated by Western blot analysis. We also identified Csrp3 in serum from 6 of 8 patients postreperfusion following acute myocardial infarction. These studies indicate that animal modeling of biomarker release using ex vivo buffer perfused tissue to limit the presence of obfuscating plasma proteins may identify candidates for further study in humans.

Mass spectrometry for protein quantification in biomarker discovery

Major technological advances have made proteomics an extremely active field for biomarker discovery in recent years due primarily to the development of newer mass spectrometric technologies and the explosion in genomic and protein bioinformatics. This leads to an increased emphasis on larger scale, faster, and more efficient methods for detecting protein biomarkers in human tissues, cells, and biofluids. Most current proteomic methodologies for biomarker discovery, however, are not highly automated and are generally labor-intensive and expensive. More automation and improved software programs capable of handling a large amount of data are essential to reduce the cost of discovery and to increase throughput. In this chapter, we discuss and describe mass spectrometry-based proteomic methods for quantitative protein analysis.

Urinary protein profiling by liquid chromatography/tandem mass spectrometry: ADAM28 is overexpressed in bladder transitional cell carcinoma

Bladder cancer is the most common urological cancer with higher incidence rate in the endemic areas of Blackfoot disease (BFD) in southern Taiwan. The aim of this study was to utilize the proteomic approach to establish urinary protein patterns of bladder cancer. The experimental results showed that most patients with bladder cancer had proteinuria or albuminuria. The urine arsenic concentrations of bladder cancer patients in BFD areas were significantly higher than those patients from non-BFD areas. In the proteomic analysis, the urinary proteome was identified by nano-high-performance liquid chromatography/electrospray ionization tandem mass spectrometry (nano-HPLC/ESI-MS/MS) followed by peptide fragmentation pattern analysis. We categorized 2782 unique proteins of which 89 proteins were identified with at least three unique matching peptide sequences. Among these 89 proteins, thirteen of them were not found in the control group and may represent proteins specific for bladder cancer. In this study, three proteins, SPINK5, ADAM28 and PTP1, were also confirmed by Western blotting and showed significant differential expression compared with the control group. ADAM28 may be used as a possible biomarker of bladder cancer.

Mass spectrometry-based approaches toward absolute quantitative proteomics

Mass spectrometry has served as a major tool for the discipline of proteomics to catalogue proteins in an unprecedented scale. With chemical and metabolic techniques for stable isotope labeling developed over the past decade, it is now routinely used as a method for relative quantification to provide valuable information on alteration of protein abundance in a proteome-wide scale. More recently, absolute or stoichiometric quantification of proteome is becoming feasible, in particular, with the development of strategies with isotope-labeled standards composed of concatenated peptides. On the other hand, remarkable progress has been also made in label-free quantification methods based on the number of identified peptides. Here we review these mass spectrometry-based approaches for absolute quantification of proteome and discuss their implications.

Proteomics-based compositional analysis of complex cellulase-hemicellulase mixtures

Efficient deconstruction of cellulosic biomass to fermentable sugars for fuel and chemical production is accomplished by a complex mixture of cellulases, hemicellulases, and accessory enzymes (e.g., >50 extracellular proteins). Cellulolytic enzyme mixtures, produced industrially mostly using fungi like Trichoderma reesei, are poorly characterized in terms of their protein composition and its correlation to hydrolytic activity on cellulosic biomass. The secretomes of commercial glycosyl hydrolase-producing microbes was explored using a proteomics approach with high-throughput quantification using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Here, we show that proteomics-based spectral counting approach is a reasonably accurate and rapid analytical technique that can be used to determine protein composition of complex glycosyl hydrolase mixtures that also correlates with the specific activity of individual enzymes present within the mixture. For example, a strong linear correlation was seen between Avicelase activity and total cellobiohydrolase content. Reliable, quantitative and cheaper analytical methods that provide insight into the cellulosic biomass degrading fungal and bacterial secretomes would lead to further improvements toward commercialization of plant biomass-derived fuels and chemicals.

A comprehensive map of the human urinary proteome

The study of the human urinary proteome has the potential to offer significant insights into normal physiology as well as disease pathology. The information obtained from such studies could be applied to the diagnosis of various diseases. The high sensitivity, resolution, and mass accuracy of the latest generation of mass spectrometers provides an opportunity to accurately catalog the proteins present in human urine, including those present at low levels. To this end, we carried out a comprehensive analysis of human urinary proteome from healthy individuals using high-resolution Fourier transform mass spectrometry. Importantly, we used the Orbitrap for detecting ions in both MS (resolution 60 000) and MS/MS (resolution 15 000) modes. To increase the depth of our analysis, we characterized both unfractionated as well as lectin-enriched proteins in our experiments. In all, we identified 1,823 proteins with less than 1% false discovery rate, of which 671 proteins have not previously been reported as constituents of human urine. This data set should serve as a comprehensive reference list for future studies aimed at identification and characterization of urinary biomarkers for various diseases.

Human urinary peptide database for multiple disease biomarker discovery

PURPOSE

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.

EXPERIMENTAL DESIGN

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.

RESULTS

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.

CONCLUSIONS AND CLINICAL RELEVANCE

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.

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.

Identification of low-abundance proteins via fractionation of the urine proteome with weak anion exchange chromatography

Background

Low-abundance proteins are difficultly observed on the two-dimensional gel electrophoresis (2-DE) maps of urine proteome, because they are usually obscured by high-abundance proteins such as albumin and immunoglobulin. In this study, a novel fractionation method was developed for enriching low-abundance proteins by removing high-abundance proteins and progressive elution with salts of various concentrations.

Results

Stepwise weak anion exchange (WAX) chromatography, which applied DEAE-Sephacel resin with non-fixed volume elution, was used to fractionate urine proteome prior to performing 2-DE. Urine proteome was separated into four fractions by progressively eluting the column with 0 M, 50 mM, 100 mM, and 1 M NaCl solutions. Most of the heavy and light immunoglobulin chains appeared in the eluent. After the high-abundance proteins were removed, various low-abundance proteins were enriched and could be easily identified. The potential of this method for obtaining diversified fractionations was demonstrated by eluting the column separately with Na₂SO₄ and MgCl₂ solutions. The 2-DE maps of the fractions eluted with these different salt solutions of identical ionic strength revealed markedly different stain patterns.

Conclusion

The present study demonstrated that this fractionation method could be applied for purposes of enriching low-abundance proteins and obtaining diversified fractionations of urine, and potentially other proteomes.

A computational method for prediction of excretory proteins and application to identification of gastric cancer markers in urine

A novel computational method for prediction of proteins excreted into urine is presented. The method is based on the identification of a list of distinguishing features between proteins found in the urine of healthy people and proteins deemed not to be urine excretory. These features are used to train a classifier to distinguish the two classes of proteins. When used in conjunction with information of which proteins are differentially expressed in diseased tissues of a specific type versus control tissues, this method can be used to predict potential urine markers for the disease. Here we report the detailed algorithm of this method and an application to identification of urine markers for gastric cancer. The performance of the trained classifier on 163 proteins was experimentally validated using antibody arrays, achieving >80% true positive rate. By applying the classifier on differentially expressed genes in gastric cancer vs normal gastric tissues, it was found that endothelial lipase (EL) was substantially suppressed in the urine samples of 21 gastric cancer patients versus 21 healthy individuals. Overall, we have demonstrated that our predictor for urine excretory proteins is highly effective and could potentially serve as a powerful tool in searches for disease biomarkers in urine in general.

Urinary CD14 as a potential biomarker for benign prostatic hyperplasia - discovery by combining MALDI-TOF-based biostatistics and ESI-MS/MS-based stable-isotope labeling

PURPOSE

Quest for specific urinary biomarkers for benign prostatic hyperplasia (BPH).

EXPERIMENTAL DESIGN

Proteomics studies were conducted with urines of the training set to discovering marker candidates that could differentiate BPH from normal subjects by matching results deduced from MALDI-TOF of individual samples and results deduced from nanoLC-ESI-MS/MS-based stable isotope dimethyl labeling of two pooled samples (BPH and normal). Samples were digested before analysis and such an approach takes into account the subject-to-subject variation and differential amount, as well as protein identification. Selected markers were validated by ELISA conducted on the training set and the test set as well as another set of urines collected from prostate cancer patients.

RESULTS

Nine marker candidates were identified from proteomics studies; CD14, prostate-specific antigen and pancreatic α-amylase precursor were further selected for ELISA validation. Urinary CD14 is among the best match with high specificity (>81%) for both training and test sets. In addition, from the study of prostate cancer patients, CD14 also allows the distinction of BPH from cancer with high specificity (84-100%) when combined with urinary prostate-specific antigen.

CONCLUSIONS AND CLINICAL RELEVANCE

Urinary CD14 is suggested to have a high specificity in the diagnosis of BPH in distinction from normal as well as cancer subjects.

Urinary proteomics: ready for prime time in urological cancer diagnostics?

The impact of clinical proteomics on the diagnosis and treatment of urological malignancies is modest in comparison with the high expectations of the past. However, most available studies suffer from flawed clinical designs rather than from technical limitations. This article will briefly introduce the main technological approaches taken, their advantages and disadvantages and will highlight the different challenges associated with urinary proteome analysis. Furthermore, several examples of the successful application of urinary clinical proteomics in the field of prostate and bladder cancer will be introduced. These examples suggest careful validation of novel biomarkers, appropriate study designs using blinded cohorts enrolled from appropriate target populations and the standardization of techniques as key elements required for successful urinary proteomics studies. These prerequisites are essential for turning the old promise of a personalized medicine approach into a new reality to optimize patients’ preventive and therapeutic care.

Utilizing spectral counting to quantitatively characterize tandem removal of abundant proteins (TRAP) in human plasma

Biomarker discovery efforts in serum and plasma are greatly hindered by the presence of high abundance proteins that prevent the detection and quantification of less abundant, yet biologically significant, proteins. The most common method for addressing this problem is to specifically remove the few abundant proteins through immunoaffinity depletion/subtraction. Herein, we improved upon this method by utilizing multiple depletion columns in series, so as to increase the efficiency of the abundant protein removal and augment the detection/identification of less abundant plasma proteins. Spectral counting was utilized to make quantitative comparisons between undepleted plasma, plasma depleted with a single depletion column, and plasma depleted using two or three depletion columns in tandem. In the undepleted plasma only 29 lower abundance protein groups were identified with the top-scoring protein from each group having a median spectral count of 3, while in the plasma processed using a single HSA depletion column 61 such protein groups were identified with a median spectral count of 8. In comparison, 76 lesser abundant protein groups were identified with a median spectral count of 11.5 in the two column setup (i.e., HSA followed by MARS Hu14). However, in the ultimate depleted plasma sample, which was created using three depletion columns in tandem, the number of less abundant protein groups identified increase to 81 and the median spectral count for the top-scoring proteins from each group increased to 15 counts per protein. Moreover, exogenous B-type natriuretic peptide-32, which was added to the plasma as a detection benchmark at 12 μg/mL, was only detected in the plasma sample depleted using three depletion columns in tandem. Collectively, these data demonstrate that this method, tandem removal of abundant proteins or TRAP, provides superior removal efficiency compared to traditional applications and improves the depth of proteome coverage in plasma.

Insights into aging through measurements of the Drosophila proteome as a function of temperature

Drosophila melanogaster is used as a model system to investigate protein changes associated with the aging process under conditions that alter organism lifespan. Changes in the proteome are assessed at various ages in populations of Oregon-R adult males that have mean lifetimes of 47 and 111 days at 28 and 18°C, respectively. Peptide hits detected from strong-cation-exchange and reversed-phase liquid chromatography coupled to tandem mass spectrometry analysis are employed to examine patterns in relative protein expression. Thirty-three proteins were identified as having similar patterns of expression at both temperatures investigated when scaling the organism age to lifespan. In addition, the proteins ferritin 2 light chain homologue and larval serum protein 1β were identified in relatively high abundance and displayed distinctly different patterns of expression between the two temperatures. Overall, the results support the notion that aspects of the aging process may be preprogrammed at the protein level.

Identification of diagnostic urinary biomarkers for acute kidney injury

Acute kidney injury (AKI) is an important cause of death among hospitalized patients. The 2 most common causes of AKI are acute tubular necrosis (ATN) and prerenal azotemia (PRA). Appropriate diagnosis of the disease is important but often difficult. We analyzed urine proteins by 2-dimensional gel electrophoresis from 38 patients with AKI. Patients were randomly assigned to a training set, an internal test set, or an external validation set. Spot abundances were analyzed by artificial neural networks to identify biomarkers that differentiate between ATN and PRA. When the trained neural network algorithm was tested against the training data, it identified the diagnosis for 16 of 18 patients in the training set and all 10 patients in the internal test set. The accuracy was validated in the novel external set of patients where conditions of 9 of 10 patients were correctly diagnosed including 5 of 5 with ATN and 4 of 5 with PRA. Plasma retinol-binding protein was identified in 1 spot and a fragment of albumin and plasma retinol-binding protein in the other. These proteins are candidate markers for diagnostic assays of AKI.