Capillary zone electrophoresis on-line coupled to mass spectrometry: A perspective application for clinical proteomics

Quantitative proteomic landscape of unstable atherosclerosis identifies molecular signatures and therapeutic targets for plaque stabilization

Atherosclerotic plaque rupture leading to myocardial infarction is a major global health burden. Applying the tandem stenosis (TS) mouse model, which distinctively exhibits the characteristics of human plaque instability/rupture, we use quantitative proteomics to understand and directly compare unstable and stable atherosclerosis. Our data highlight the disparate natures and define unique protein signatures of unstable and stable atherosclerosis. Key proteins and pathway networks are identified such as the innate immune system, and neutrophil degranulation. The latter includes calprotectin S100A8/A9, which we validate in mouse and human unstable plaques, and we demonstrate the plaque-stabilizing effects of its inhibition. Overall, we provide critical insights into the unique proteomic landscape of unstable atherosclerosis (as distinct from stable atherosclerosis and vascular tissue). We further establish the TS model as a reliable preclinical tool for the discovery and testing of plaque-stabilizing drugs. Finally, we provide a knowledge resource defining unstable atherosclerosis that will facilitate the identification and validation of long-sought-after therapeutic targets and drugs for plaque stabilization.

Proteomics profiling of kidney brush border membrane from rats using LC-MS/MS analysis

PURPOSE

Chronic kidney disease (CKD) is defined by a reduced renal function, that is, glomerular filtration rate, and the extent of kidney damage is assessed by determining serum creatinine levels and proteins in urine, diagnosed as proteinuria/albuminuria. Albuminuria increases with age and can result from glomerular and/or proximal tubule (PT) alterations. Brush border membranes (BBMs) on PT cells are important in maintaining the stability of PT functions.

EXPERIMENTAL DESIGN

An LC-MS/MS bottom-up proteomics analysis of BBMs from four groups of rat models was applied to investigate protein abundance alterations associated with CKD progression. Moreover, systems biology analyses were used to identify key proteins that can provide insight into the different regulated molecular pathways and processes associated with CKD.

RESULTS

Our results indicated that 303 proteins showed significantly altered expressions from the severe CKD BBM group when compared to the control. Focusing on renal diseases, several proteins including Ctnnb1, Fah, and Icam1 were annotated to kidney damage and urination disorder. The up-regulation of Ctnnb1 (β-catenin) could contribute to CKD through the regulation of the WNT signaling pathway.

CONCLUSION AND CLINICAL RELEVANCE

Overall, the study of protein abundance changes in BBMs from rat models helps to reveal protein corrections with important pathways and regulator effects involved in CKD. Although this study is focused on rat models, the results provided more information for a deeper insight into possible CKD mechanisms in humans.

LC-MS/MS-Based Proteomics Approach for the Identification of Candidate Serum Biomarkers in Patients with Narcolepsy Type 1

Narcolepsy type 1 (NT1) is the most common type of narcolepsy known to be caused by the loss of specific neurons responsible for producing peptide neurotransmitters (orexins/hypocretins), resulting in a sleep-wake cycle disorder. It is characterized by its association with cataplexy and abnormalities in rapid eye movement. To date, no cure has been established for this life-threatening condition. Misdiagnosis of NT1 is also quite common, although it is not exceedingly rare. Therefore, successfully identifying candidate serum biomarkers for NT1 would be a head start for accurate diagnosis and development of therapeutics for this disorder. This study aims to identify such potential serum biomarkers. A depletion protocol was employed for 27 human serum samples (16 NT1 and 11 healthy controls), followed by applying LC-MS/MS bottom-up proteomics analysis, then LC-PRM-MS for validation. The comparison of the proteome profiles of the low-abundant proteins in the samples was then investigated based on age, sex, sample groups, and the presence of the Human Leukocyte Antigen (HLA) DQB1*0602 allele. The results were tracked to gene expression studies as well as system biology to identify key proteins and understand their relationship in the pathogenesis of NT1. Our results revealed 36 proteins significantly and differentially expressed. Among the impaired pathways and bioprocesses, the complement activation pathway is impaired by six of the differentially expressed proteins (DEPs). They are coded by the genes C2, CFB, C5, C1R, C1S, and MASP1, while 11 DEPs are involved in Acute Phase Response Signaling (APRS), which are coded by the genes FN1, AMBP, APOH, CFB, CP, ITIH2, C5, C2, F2, C1, and ITIH4. The combined AUCs of the downregulated and upregulated DEPs are 0.95 and 0.76, respectively. Overall, this study reveals potential serum-protein biomarkers of NT1 and explains the possible correlation between the biomarkers and pathophysiological effects, as well as important biochemical pathways involved in NT1.

A urinary peptidomics approach for early stages of cardiovascular disease risk: The African-PREDICT study

Cardiovascular disease (CVD) affects individuals across the lifespan, with multiple cardiovascular (CV) risk factors increasingly present in young populations. The underlying mechanisms in early cardiovascular disease development are complex and still poorly understood. We therefore employed urinary proteomics as a novel approach to gain better insight into early CVD-related molecular pathways based on a CVD risk stratification approach. This study included 964 apparently healthy (no self-reported chronic illnesses, free from clinical symptoms of CVD) black and white men and women (aged 20-30 years old) from the African Prospective study on the Early Detection and Identification of Cardiovascular disease and Hypertension (African-PREDICT) study. Cardiovascular risk factors used for stratification included obesity, physical inactivity, tobacco use, high alcohol intake, hyperglycemia, dyslipidemia and hypertension. Participants were divided into low (0 risk factors), medium (1-2 risk factors) and high (≥3 risk factors) CV risk groups. We analyzed urinary peptidomics by capillary electrophoresis time-of-flight mass spectrometry. After adjusting for ethnicity, sex and age, 65 sequenced urinary peptides were differentially expressed between the CV risk groups (all q-values ≤ 0.01). These peptides included a lower abundance of collagen type I- and III-derived peptides in the high compared to the low CV risk group. With regard to noncollagen peptides, we found a lower abundance of alpha-1-antitrypsin fragments in the high compared to the low CV risk group (all q-values ≤ 0.01). Our findings indicate lower abundances of collagen types I and III in the high compared to the low CV risk group, suggesting potential early alterations in the CV extracellular matrix.

Advances in capillary electrophoresis for the life sciences

Capillary electrophoresis (CE) played an important role in developments in the life sciences. The technique is nowadays used for the analysis of both large and small molecules in applications where it performs better than or is complementary to liquid chromatographic techniques. In this review, principles of different electromigration techniques, especially capillary isoelectric focusing (CIEF), capillary gel (CGE) and capillary zone electrophoresis (CZE), are described and recent developments in instrumentation, with an emphasis on mass spectrometry (MS) coupling and microchip CE, are discussed. The role of CE in the life sciences is shown with applications in which it had a high impact over the past few decades. In this context, current practice for the characterization of biopharmaceuticals (therapeutic proteins) is shown with CIEF, CGE and CZE using different detection techniques, including MS. Subsequently, the application of CGE and CZE, in combination with laser induced fluorescence detection and CZE-MS are demonstrated for the analysis of protein-released glycans in the characterization of biopharmaceuticals and glycan biomarker discovery in biological samples. Special attention is paid to developments in capillary coatings and derivatization strategies for glycans. Finally, routine CE analysis in clinical chemistry and latest developments in metabolomics approaches for the profiling of small molecules in biological samples are discussed. The large number of CE applications published for these topics in recent years clearly demonstrates the established role of CE in life sciences.

Urinary Proteomics as a Tool to Identify Kidney Responders to Dipeptidyl Peptidase-4 Inhibition: A Hypothesis-Generating Analysis from the MARLINA-T2D Trial

PURPOSE

Chronic kidney disease (CKD) is a serious complication of hyperglycemia and treatment options to slow its progression are scarce. Dipeptidyl peptidase-4 (DPP-4) inhibitors are common glucose-lowering drugs in type 2 diabetes (T2D). Among these, linagliptin has been suggested to exert kidney protective effects. It is investigated whether an effect of linagliptin on kidney function could be unmasked by characterizing the urinary proteome profile (UPP) in albuminuric T2D individuals.

EXPERIMENTAL DESIGN

Participants of the MARLINA-T2D trial (NCT01792518) are randomized 1:1 to receive either linagliptin 5 mg or placebo for 24 weeks. A previously developed proteome-based classifier, CKD273, is assessed.

RESULTS

Results confirm a significant correlation between CKD273 and clinical kidney parameters as well as with eGFR decline. Patient stratification using CKD273 at baseline, show a trend toward attenuation of renal function loss in high CKD-risk patients treated with linagliptin. Moreover, characterized are linagliptin affected peptides of which the majority contained a DPP-4 target sequence.

CONCLUSIONS AND CLINICAL RELEVANCE

CKD273 is a promising tool for identifying patients at high risk for CKD progression and may unmask a potential of linagliptin to slow progressive kidney function loss in high CKD-risk patients. UPP characterization reveals a significant impact of linagliptin on urinary peptides.

Sheathless Capillary Electrophoresis-Mass Spectrometry for the Profiling of Charged Metabolites in Biological Samples

Capillary electrophoresis (CE) is well suited for the profiling of highly polar and charged metabolites as compounds are separated on the basis of their charge-to-size ratio. The protocol presented here is based on using a recently developed sheathless interfacing design, i.e., a porous tip interface, for coupling CE to electrospray ionization mass spectrometry (MS). It is demonstrated that sheathless CE-MS employing a bare fused-silica capillary at low-pH separation conditions can be used for the profiling of both cationic and anionic metabolites by only switching the MS detection and electrophoretic separation voltage polarity. The proposed sheathless CE-MS protocol allows efficient and sensitive profiles to be obtained for a broad array of charged metabolites, including amino acids, organic acids, nucleotides, and sugar phosphates, in various biological samples, such as urine and extracts of the glioblastoma cell line.

Urinary proteomic biomarkers in oncology: ready for implementation?

Introduction: Biomarkers are expected to improve the management of cancer patients by enabling early detection and prediction of therapeutic response. Proteins reflect a molecular phenotype, have high potential as biomarkers, and also are key targets for intervention. Given the ease of collection and proximity to certain tumors, the urinary proteome is a rich source of biomarkers and several proteins have been already implemented. Areas covered: We examined the literature on urine proteins and proteome analysis in oncology from reports published during the last 5 years to generate an overview on the status of urine protein and peptide biomarkers, with emphasis on their actual clinical value. Expert commentary: A few studies report on biomarkers that are ready to be implemented in patient management, among others in bladder cancer and cholangiocarcinoma. These reports are based on multi-marker approaches. A high number of biomarkers, though, has been described in studies with low statistical power. In fact, several of them have been consistently reported across different studies. The latter should be the focus of attention and be tested in properly designed confirmatory and ultimately, prospective investigations. It is expected that multi-marker classifiers for a specific context-of-use, will be the preferred path toward clinical implementation.

Urinary Glycopeptide Analysis for the Investigation of Novel Biomarkers

PURPOSE

Urine is a rich source of potential biomarkers, including glycoproteins. Glycoproteomic analysis remains difficult due to the high heterogeneity of glycans. Nevertheless, recent advances in glycoproteomics software solutions facilitate glycopeptide identification and characterization. The aim is to investigate intact glycopeptides in the urinary peptide profiles of normal subjects using a novel PTM-centric software-Byonic.

EXPERIMENTAL DESIGN

The urinary peptide profiles of 238 normal subjects, previously analyzed using CE-MS and CE-MS/MS and/or LC-MS/MS, are subjected to glycopeptide analysis. Additionally, glycopeptide distribution is assessed in a set of 969 patients with five different cancer types: bladder, prostate and pancreatic cancer, cholangiocarcinoma, and renal cell carcinoma.

RESULTS

A total of 37 intact O-glycopeptides and 23 intact N-glycopeptides are identified in the urinary profiles of 238 normal subjects. Among the most commonly identified O-glycoproteins are Apolipoprotein C-III and insulin-like growth factor II, while titin among the N-glycoproteins. Further statistical analysis reveals that three O-glycopeptides and five N-glycopeptides differed significantly in their abundance among the different cancer types, comparing to normal subjects.

CONCLUSIONS AND CLINICAL RELEVANCE

Through the established glycoproteomics workflow, intact O- and N-glycopeptides in human urine are identified and characterized, providing novel insights for further exploration of the glycoproteome with respect to specific diseases.

Clinical Proteomics: Closing the Gap from Discovery to Implementation

Clinical proteomics, the application of proteome analysis to serve a clinical purpose, represents a major field in the area of proteome research. Over 1000 manuscripts on this topic are published each year, with numbers continuously increasing. However, the anticipated outcome, the transformation of the reported findings into improvements in patient management, is not immediately evident. In this article, the value and validity of selected clinical proteomics findings are investigated, and it is assessed how far implementation has progressed. A main conclusion from this assessment is that to achieve implementation, well-powered clinical studies are required in the appropriate population, addressing a specific clinical need and with a clear context-of-use. Efforts toward implementation, to be feasible, must be supported by the key players in science: publishers and funders. The authors propose a change on objectives, from additional discovery studies toward studies aiming at validation of the plethora of potential biomarkers that have been described, to demonstrate practical value of clinical proteomics. All elements required, potential biomarkers, technologies, and bio-banked samples are available (based on today's literature), hence a change in focus from discovery toward validation and application is not only urgently necessary, but also possible based on resources available today.

Urinary proteomics using capillary electrophoresis coupled to mass spectrometry for diagnosis and prognosis in kidney diseases

PURPOSE OF REVIEW

Urine is the most useful of body fluids for biomarker research. Therefore, we have focused on urinary proteomics, using capillary electrophoresis coupled to mass spectrometry, to investigate kidney diseases in recent years.

RECENT FINDINGS

Several urinary proteomics studies for the detection of various kidney diseases have indicated the potential of this approach aimed at diagnostic and prognostic assessment. Urinary protein biomarkers such as collagen fragments, serum albumin, α-1-antitrypsin, and uromodulin can help to explain the processes involved during disease progression.

SUMMARY

Urinary proteomics has been used in several studies in order to identify and validate biomarkers associated with different kidney diseases. These biomarkers, with improved sensitivity and specificity when compared with the current gold standards, provide a significant alternative for diagnosis and prognosis, as well as improving clinical decision-making.

Recent developments in capillary and microchip electroseparations of peptides (2015-mid 2017)

The review brings a comprehensive overview of recent developments and applications of high performance capillary and microchip electroseparation methods (zone electrophoresis, isotachophoresis, isoelectric focusing, affinity electrophoresis, electrokinetic chromatography, and electrochromatography) to analysis, microscale isolation, purification, and physicochemical and biochemical characterization of peptides in the years 2015, 2016, and ca. up to the middle of 2017. Advances in the investigation of electromigration properties of peptides and in the methodology of their analysis (sample preseparation, preconcentration and derivatization, adsorption suppression and EOF control, and detection) are described. New developments in particular CE and CEC methods are presented and several types of their applications to peptide analysis are reported: qualitative and quantitative analysis, determination in complex (bio)matrices, monitoring of chemical and enzymatical reactions and physical changes, amino acid, sequence and chiral analysis, and peptide mapping of proteins. Some micropreparative peptide separations are shown and capabilities of CE and CEC methods to provide important physicochemical characteristics of peptides are demonstrated.

Recent advances in CE and microchip-CE in clinical applications: 2014 to mid-2017

CE and microchip CE (ME) are powerful tools for the analysis of a number of different analytes and have been applied to a variety of clinical fields and human samples. This review will present an overview of the most recent applications of these techniques to different areas of clinical medicine during the period of 2014 to mid-2017. CE and ME have been applied to clinical chemistry, drug detection and monitoring, hematology, infectious diseases, oncology, endocrinology, neonatology, nephrology, and genetic screening. Samples examined range from serum, plasma, and urine to lest utilized materials such as tears, cerebral spinal fluid, sweat, saliva, condensed breath, single cells, and biopsy tissue. Examples of clinical applications will be given along with the various detection systems employed.

Prediction of acute coronary syndromes by urinary proteome analysis

Identification of individuals who are at risk of suffering from acute coronary syndromes (ACS) may allow to introduce preventative measures. We aimed to identify ACS-related urinary peptides, that combined as a pattern can be used as prognostic biomarker. Proteomic data of 252 individuals enrolled in four prospective studies from Australia, Europe and North America were analyzed. 126 of these had suffered from ACS within a period of up to 5 years post urine sampling (cases). Proteomic analysis of 84 cases and 84 matched controls resulted in the discovery of 75 ACS-related urinary peptides. Combining these to a peptide pattern, we established a prognostic biomarker named Acute Coronary Syndrome Predictor 75 (ACSP75). ACSP75 demonstrated reasonable prognostic discrimination (c-statistic = 0.664), which was similar to Framingham risk scoring (c-statistics = 0.644) in a validation cohort of 42 cases and 42 controls. However, generating by a composite algorithm named Acute Coronary Syndrome Composite Predictor (ACSCP), combining the biomarker pattern ACSP75 with the previously established urinary proteomic biomarker CAD238 characterizing coronary artery disease as the underlying aetiology, and age as a risk factor, further improved discrimination (c-statistic = 0.751) resulting in an added prognostic value over Framingham risk scoring expressed by an integrated discrimination improvement of 0.273 ± 0.048 (P < 0.0001) and net reclassification improvement of 0.405 ± 0.113 (P = 0.0007). In conclusion, we demonstrate that urinary peptide biomarkers have the potential to predict future ACS events in asymptomatic patients. Further large scale studies are warranted to determine the role of urinary biomarkers in clinical practice.

Urinary biomarkers for renal tract malformations

INTRODUCTION

Renal tract malformations (RTMs) are congenital anomalies of the kidneys and urinary tract, which are the major cause of end-stage renal disease in children. Using immunoassay-based approaches (ELISA, western blot), individual urinary proteins including transforming growth factor β, tumor necrosis factor and monocyte attractant proteins 1 were found to be associated to RTMs. However, only mass spectrometry (MS) based methods leading to the identification of panels of protein-based markers composed of fragments of the extracellular matrix allowed the prediction of progression of RTMs and its complications. Areas covered: In this review, we summarized relevant studies identified in "Pubmed" using the keywords "urinary biomarkers" and "proteomics" and "renal tract malformations" or "hydronephrosis" or "ureteropelvic junction obstruction" or "posterior urethral valves" or "vesicoureteral reflux". These publications represent studies on potential protein-based biomarkers, either individually or combined in panels, of RTMs in human and animal models. Expert commentary: Successful use in the clinic of these protein-based biomarkers will need to involve larger scale studies to reach sufficient power. Improved performance will potentially come from combining immunoassay- and MS-based markers.

CE-MS for metabolomics: Developments and applications in the period 2014-2016

CE–MS can be considered a useful analytical technique for the global profiling of (highly) polar and charged metabolites in various samples. Over the past few years, significant advancements have been made in CE–MS approaches for metabolomics studies. In this paper, which is a follow‐up of a previous review paper covering the years 2012–2014 (Electrophoresis 2015, 36, 212–224), recent CE–MS strategies developed for metabolomics covering the literature from July 2014 to June 2016 are outlined. Attention will be paid to new CE–MS approaches for the profiling of anionic metabolites and the potential of SPE coupled to CE–MS is also demonstrated. Representative examples illustrate the applicability of CE–MS in the fields of biomedical, clinical, microbial, plant, and food metabolomics. A complete overview of recent CE–MS‐based metabolomics studies is given in a table, which provides information on sample type and pretreatment, capillary coatings, and MS detection mode. Finally, general conclusions and perspectives are given.

Identification of ageing-associated naturally occurring peptides in human urine

To assess normal and pathological peptidomic changes that may lead to an improved understanding of molecular mechanisms underlying ageing, urinarypeptidomes of 1227 healthy and 10333 diseased individuals between 20 and 86 years of age were investigated. The diseases thereby comprised diabetes mellitus, renal and cardiovascular diseases. Using age as a continuous variable, 116 peptides were identified that significantly (p < 0.05; |ρ|≥0.2) correlated with age in the healthy cohort. The same approach was applied to the diseased cohort. Upon comparison of the peptide patterns of the two cohorts 112 common age-correlated peptides were identified. These 112 peptides predominantly originated from collagen, uromodulin and fibrinogen. While most fibrillar and basement membrane collagen fragments showed a decreased age-related excretion, uromodulin, beta-2-microglobulin and fibrinogen fragments showed an increase. Peptide-based in silico protease analysis was performed and 32 proteases, including matrix metalloproteinases and cathepsins, were predicted to be involved in ageing. Identified peptides, predicted proteases and patient information were combined in a systems biology pathway analysis to identify molecular pathways associated with normal and/or pathological ageing. While perturbations in collagen homeostasis, trafficking of toll-like receptors and endosomal pathways were commonly identified, degradation of insulin-like growth factor-binding proteins was uniquely identified in pathological ageing.

Urinary Proteomics Pilot Study for Biomarker Discovery and Diagnosis in Heart Failure with Reduced Ejection Fraction

Background

Biomarker discovery and new insights into the pathophysiology of heart failure with reduced ejection fraction (HFrEF) may emerge from recent advances in high-throughput urinary proteomics. This could lead to improved diagnosis, risk stratification and management of HFrEF.

Methods and Results

Urine samples were analyzed by on-line capillary electrophoresis coupled to electrospray ionization micro time-of-flight mass spectrometry (CE-MS) to generate individual urinary proteome profiles. In an initial biomarker discovery cohort, analysis of urinary proteome profiles from 33 HFrEF patients and 29 age- and sex-matched individuals without HFrEF resulted in identification of 103 peptides that were significantly differentially excreted in HFrEF. These 103 peptides were used to establish the support vector machine-based HFrEF classifier HFrEF103. In a subsequent validation cohort, HFrEF103 very accurately (area under the curve, AUC = 0.972) discriminated between HFrEF patients (N = 94, sensitivity = 93.6%) and control individuals with and without impaired renal function and hypertension (N = 552, specificity = 92.9%). Interestingly, HFrEF103 showed low sensitivity (12.6%) in individuals with diastolic left ventricular dysfunction (N = 176). The HFrEF-related peptide biomarkers mainly included fragments of fibrillar type I and III collagen but also, e.g., of fibrinogen beta and alpha-1-antitrypsin.

Conclusion

CE-MS based urine proteome analysis served as a sensitive tool to determine a vast array of HFrEF-related urinary peptide biomarkers which might help improving our understanding and diagnosis of heart failure.

Acute kidney injury prediction in cardiac surgery patients by a urinary peptide pattern: a case-control validation study

Background

Acute kidney injury (AKI) is a prominent problem in hospitalized patients and associated with increased morbidity and mortality. Clinical medicine is currently hampered by the lack of accurate and early biomarkers for diagnosis of AKI and the evaluation of the severity of the disease.

In 2010, we established a multivariate peptide marker pattern consisting of 20 naturally occurring urinary peptides to screen patients for early signs of renal failure. The current study now aims to evaluate if, in a different study population and potentially various AKI causes, AKI can be detected early and accurately by proteome analysis.

Methods

Urine samples from 60 patients who developed AKI after cardiac surgery were analyzed by capillary electrophoresis-mass spectrometry (CE-MS). The obtained peptide profiles were screened by the AKI peptide marker panel for early signs of AKI. Accuracy of the proteomic model in this patient collective was compared to that based on urinary neutrophil gelatinase-associated lipocalin (NGAL) and kidney injury molecule-1 (KIM-1) ELISA levels. Sixty patients who did not develop AKI served as negative controls.

Results

From the 120 patients, 110 were successfully analyzed by CE-MS (59 with AKI, 51 controls). Application of the AKI panel demonstrated an AUC in receiver operating characteristics (ROC) analysis of 0.81 (95 % confidence interval: 0.72–0.88). Compared to the proteomic model, ROC analysis revealed poorer classification accuracy of NGAL and KIM-1 with the respective AUC values being outside the statistical significant range (0.63 for NGAL and 0.57 for KIM-1).

Conclusions

This study gives further proof for the general applicability of our proteomic multimarker model for early and accurate prediction of AKI irrespective of its underlying disease cause.

Electronic supplementary material

The online version of this article (doi:10.1186/s13054-016-1344-z) contains supplementary material, which is available to authorized users.

Implementation of CE-MS-identified proteome-based biomarker panels in drug development and patient management

The recent advancements in clinical proteomics enabled identification of biomarker panels for a large range of diseases. A number of CE-MS-identified biomarker panels were verified and implemented in clinical studies. Despite multiple challenges, accumulating evidence supports the value and the need for proteome-based biomarker panels. In this perspective, we provide an overview of clinical studies indicating the added value of CE-MS biomarker panels over traditional diagnostics and monitoring methods. We outline apparent advantages of applying novel proteomic biomarker panels for disease diagnosis, prognosis, staging, drug development and patient management. Facing the plethora of benefits associated with the use of CE-MS biomarker panels, we envision their implementation into the medical practice in the near future.

Biomarker discovery in mass spectrometry-based urinary proteomics

Urinary proteomics has become one of the most attractive topics in disease biomarker discovery. MS-based proteomic analysis has advanced continuously and emerged as a prominent tool in the field of clinical bioanalysis. However, only few protein biomarkers have made their way to validation and clinical practice. Biomarker discovery is challenged by many clinical and analytical factors including, but not limited to, the complexity of urine and the wide dynamic range of endogenous proteins in the sample. This article highlights promising technologies and strategies in the MS-based biomarker discovery process, including study design, sample preparation, protein quantification, instrumental platforms, and bioinformatics. Different proteomics approaches are discussed, and progresses in maximizing urinary proteome coverage and standardization are emphasized in this review. MS-based urinary proteomics has great potential in the development of noninvasive diagnostic assays in the future, which will require collaborative efforts between analytical scientists, systems biologists, and clinicians.

Capillary Electrophoresis-Mass Spectrometry for Clinical Metabolomics

In clinical metabolomics, capillary electrophoresis-mass spectrometry (CE-MS) has become a very useful technique for the analysis of highly polar and charged metabolites in complex biologic samples. A comprehensive overview of recent developments in CE-MS for metabolic profiling studies is presented. This review covers theory, CE separation modes, capillary coatings, and practical aspects of CE-MS coupling. Attention is also given to sample pretreatment and data analysis strategies used for metabolomics. The applicability of CE-MS for clinical metabolomics is illustrated using samples ranging from plasma and urine to cells and tissues. CE-MS application to large-scale and quantitative clinical metabolomics is addressed. Conclusions and perspectives on this unique analytic strategy are presented.