Detection of Proteoforms Using Top-Down Mass Spectrometry and Diagnostic Ions.

Characterization of protein structure modifications is an important field in mass spectrometry (MS)-based proteomics. Here, we describe a process to quickly and reliably identify a mass change in a targeted protein sequence by top-down mass spectrometry (TD MS) using electron transfer dissociation (ETD). The step-by-step procedure describes how to develop a TD MS method for data acquisition as well as the data analysis process. The described TD MS workflow utilizes diagnostic ions to characterize an unknown sample in a few hours.

Clinical method evaluation of hemoglobin S and C identification by top-down selected reaction monitoring and electron transfer dissociation.

BACKGROUND: Biological diagnosis of hemoglobin disorders is a complex process relying on the combination of several analytical techniques to identify Hb variants in a particular sample. Currently, hematology laboratories usually use high-performance liquid chromatography (HPLC), capillary electrophoresis and gel-based methods to characterize Hb variants. Co-elution and co-migration may represent major issues for precise identification of Hb variants, even for the most common ones such as Hb S and C. METHODS: We adapted a top-down selected reaction monitoring (SRM) electron transfer dissociation (ETD) mass spectrometry (MS) method to fit with a clinical laboratory environment. An automated analytical process with semi-automated data analysis compatible with a clinical practice was developed. A comparative study between a reference HPLC method and the MS assay was performed on 152 patient samples. RESULTS: The developed workflow allowed to identify with high specificity and selectivity the most common Hb variants (Hb S and Hb C). Concordance of the MS-based approach with HPLC was 71/71 (100%) for Hb S and 11/11 (100%) for Hb C. CONCLUSIONS: This top-down SRM ETD method can be used in a clinical environment to detect Hb S and Hb C.

Accessing Reliable Health Information on the Web: A Review of the HON Approach.

Accessing online health content of high quality and reliability presents challenges. Laypersons cannot easily differentiate trustworthy content from misinformed or manipulated content. This article describes complementary approaches for members of the general public and health professionals to find trustworthy content with as little bias as possible. These include the Khresmoi health search engine (K4E), the Health On the Net Code of Conduct (HONcode) and health trust indicator Web browser extensions.

Health On the Net's 20 Years of Transparent and Reliable Health Information.

The Health On the Net Foundation (HON) was born in 1996, during the beginning of the World Wide Web, from a collective decision by health specialists, led by the late Jean-Raoul Scherrer, who anticipated the need for online trustworthy health information. Because the Internet is a free space that everyone shares, a search for quality information is like a shot in the dark: neither will reliably hit their target. Thus, HON was created to promote deployment of useful and reliable online health information, and to enable its appropriate and efficient use. Two decades on, HON is the oldest and most valued quality marker for online health information. The organization has maintained its reputation through dynamic measures, innovative endeavors and dedication to upholding key values and goals. This paper provides an overview of the HON Foundation, and its activities, challenges, and achievements over the years.

Evaluation and identification of dioxin exposure biomarkers in human urine by high-resolution metabolomics, multivariate analysis and in vitro synthesis.

A previous high-resolution metabolomic study pointed out a dysregulation of urinary steroids and bile acids in human cases of acute dioxin exposure. A subset of 24 compounds was highlighted as putative biomarkers. The aim of the current study was (i) to evaluate the 24 biomarkers in an independent human cohort exposed to dioxins released from the incineration fumes of a municipal waste incinerator and; (ii) to identify them by comparison with authentic chemical standards and biosynthesised products obtained with in vitro metabolic reactions. An orthogonal projection to latent structures discriminant analysis built on biomarker profiles measured in the intoxicated cohort and the controls separated both groups with reported values of 93.8%; 100% and 87.5% for global accuracy; sensitivity and specificity; respectively. These results corroborated the 24 compounds as exposure biomarkers; but a definite identification was necessary for a better understanding of dioxin toxicity. Dehydroepiandrosterone 3ß-sulfate, androsterone 3α-glucuronide, androsterone 3α-sulfate, pregnanediol 3α-glucuronide and 11-ketoetiocholanolone 3α-glucuronide were identified by authentic standards. Metabolic reactions characterised four biomarkers: glucuronide conjugates of 11ß-hydroxyandrosterone; glycochenodeoxycholic acid and glycocholic acid produced in human liver microsomes and glycoursodeoxycholic acid sulfate generated in cytosol fraction. The combination of metabolomics by high-resolution mass spectrometry with in vitro metabolic syntheses confirmed a perturbed profile of steroids and bile acids in human cases of dioxin exposure.

Quantification of HER2 by Targeted Mass Spectrometry in Formalin-Fixed Paraffin-Embedded (FFPE) Breast Cancer Tissues.

The ability to accurately quantify proteins in formalin-fixed paraffin-embedded tissues using targeted mass spectrometry opens exciting perspectives for biomarker discovery. We have developed and evaluated a selectedreaction monitoring assay for the human receptor tyrosine-protein kinase erbB-2 (HER2) in formalin-fixed paraffin-embedded breast tumors. Peptide candidates were identified using an untargeted mass spectrometry approach in relevant cell lines. A multiplexed assay was developed for the six best candidate peptides and evaluated for linearity, precision and lower limit of quantification. Results showed a linear response over a calibration range of 0.012 to 100 fmol on column (R(2): 0.99-1.00).The lower limit of quantification was 0.155 fmol on column for all peptides evaluated. The six HER2 peptides were quantified by selected reaction monitoring in a cohort of 40 archival formalin-fixed paraffin-embedded tumor tissues from women with invasive breast carcinomas, which showed different levels of HER2 gene amplification as assessed by standard methods used in clinical pathology. The amounts of the six HER2 peptides were highly and significantly correlated with each other, indicating that peptide levels can be used as surrogates of protein amounts in formalin-fixed paraffin-embedded tissues. After normalization for sample size, selected reaction monitoring peptide measurements were able to correctly predict 90% of cases based on HER2 amplification as defined by the American Society of Clinical Oncology and College of American Pathologists. In conclusion, the developed assay showed good analytical performance and a high agreement with immunohistochemistry and fluorescence in situ hybridization data. This study demonstrated that selected reaction monitoring allows to accurately quantify protein expression in formalin-fixed paraffin-embedded tissues and represents therefore a powerful approach for biomarker discovery studies. The untargeted mass spectrometry data is available via ProteomeXchange whereas the quantification data by selected reaction monitoring is available on the Panorama Public website.

Steroidomic Footprinting Based on Ultra-High Performance Liquid Chromatography Coupled with Qualitative and Quantitative High-Resolution Mass Spectrometry for the Evaluation of Endocrine Disrupting Chemicals in H295R Cells.

The screening of endocrine disrupting chemicals (EDCs) that may alter steroidogenesis represents a highly important field mainly due to the numerous pathologies, such as cancer, diabetes, obesity, osteoporosis, and infertility that have been related to impaired steroid-mediated regulation. The adrenal H295R cell model has been validated to study steroidogenesis by the Organization for Economic Co-operation and Development (OECD) guideline. However, this guideline focuses solely on testosterone and estradiol monitoring, hormones not typically produced by the adrenals, hence limiting possible in-depth mechanistic investigations. The present work proposes an untargeted steroidomic footprinting workflow based on ultra-high pressure liquid chromatography (UHPLC) coupled to high-resolution MS for the screening and mechanistic investigations of EDCs in H295R cell supernatants. A suspected EDC, triclocarban (TCC), used in detergents, cosmetics, and personal care products, was selected to demonstrate the efficiency of the reported methodology, allowing the simultaneous assessment of a steroidomic footprint and quantification of a selected subset of steroids in a single analysis. The effects of exposure to increasing TCC concentrations were assessed, and the selection of features with database matching followed by multivariate analysis has led to the selection of the most salient affected steroids. Using correlation analysis, 11 steroids were associated with a high, 18 with a medium, and 8 with a relatively low sensitivity behavior to TCC. Among the candidates, 13 identified steroids were simultaneously quantified, leading to the evaluation and localization of the disruption of steroidogenesis caused by TCC upstream of the formation of pregnenolone. The remaining candidates could be associated with a specific steroid class (progestogens and corticosteroids, or androgens) and represent a specific footprint of steroidogenesis disruption by TCC. This strategy was devised to be compatible with medium/high-throughput screening and could be useful for the mechanistic elucidation of EDCs.

Identification of hemoglobin variants by top-down mass spectrometry using selected diagnostic product ions.

Hemoglobin disorder diagnosis is a complex procedure combining several analytical steps. Due to the lack of specificity of the currently used protein analysis methods, the identification of uncommon hemoglobin variants (proteoforms) can become a hard task to accomplish. The aim of this work was to develop a mass spectrometry-based approach to quickly identify mutated protein sequences within globin chain variants. To reach this goal, a top-down electron transfer dissociation mass spectrometry method was developed for hemoglobin ß chain analysis. A diagnostic product ion list was established with a color code strategy allowing to quickly and specifically localize a mutation in the hemoglobin ß chain sequence. The method was applied to the analysis of rare hemoglobin ß chain variants and an (A)γ-ß fusion protein. The results showed that the developed data analysis process allows fast and reliable interpretation of top-down electron transfer dissociation mass spectra by nonexpert users in the clinical area.

Assessment of the influence of the patient's inflammatory state on the accuracy of a haptoglobin selected reaction monitoring assay.

BACKGROUND: The use of targeted LC-MS/MS methods for protein quantitation in clinical laboratories implies a careful evaluation of potential sources of analytical interference. In this study, we investigated whether inflammation, which is associated with both the release of proteolytic enzymes and increased expression of acute phase protease inhibitors, is affecting the accuracy of a haptoglobin selected reaction monitoring (SRM) assay. RESULTS: A SRM assay was developed and used to quantify haptoglobin in 57 human serum samples. The SRM assay had CVs (n = 6) of 12.9% at 698 mg/L and 11.8% at 1690 mg/L. Results of the SRM assay were compared to those of a commercial immunonephelometric test. Passing-Bablok regression gave a proportional bias of 0.92 (95% CI: 0.82 to 1.04) and a constant bias of 75.40 (95% CI: -71.09 to 251.04), indicating that SRM and immunonephelometric assays provided comparable results. We then investigated whether the accuracy of the SRM assay was influenced by the patient's inflammatory state by assessing the relationship between the serum CRP concentration and the bias between the two methods. No correlation was found between the SRM/immunoassay bias and the CRP concentration (Pearson correlation coefficient r = 0.0898). CONCLUSIONS: These data indicate that neither the release of proteolytic enzymes nor the increased level of protease inhibitors occurring during inflammation processes have a significant impact on the haptoglobin SRM assay accuracy. Such studies provide important information about potential sources of analytical interferences in protein SRM assays.

Human urinary biomarkers of dioxin exposure: analysis by metabolomics and biologically driven data dimensionality reduction.

Untargeted metabolomic approaches offer new opportunities for a deeper understanding of the molecular events related to toxic exposure. This study proposes a metabolomic investigation of biochemical alterations occurring in urine as a result of dioxin toxicity. Urine samples were collected from Czech chemical workers submitted to severe dioxin occupational exposure in a herbicide production plant in the late 1960s. Experiments were carried out with ultra-high pressure liquid chromatography (UHPLC) coupled to high-resolution quadrupole time-of-flight (QTOF) mass spectrometry. A chemistry-driven feature selection was applied to focus on steroid-related metabolites. Supervised multivariate data analysis allowed biomarkers, mainly related to bile acids, to be highlighted. These results supported the hypothesis of liver damage and oxidative stress for long-term dioxin toxicity. As a second step of data analysis, the information gained from the urine analysis of Victor Yushchenko after his poisoning was examined. A subset of relevant urinary markers of acute dioxin toxicity from this extreme phenotype, including glucuro- and sulfo-conjugated endogenous steroid metabolites and bile acids, was assessed for its ability to detect long-term effects of exposure. The metabolomic strategy presented in this work allowed the determination of metabolic patterns related to dioxin effects in human and the discovery of highly predictive subsets of biologically meaningful and clinically relevant compounds. These results are expected to provide valuable information for a deeper understanding of the molecular events related to dioxin toxicity. Furthermore, it presents an original methodology of data dimensionality reduction by using extreme phenotype as a guide to select relevant features prior to data modeling (biologically driven data reduction).

Bile carcinoembryonic cell adhesion molecule 6 (CEAM6) as a biomarker of malignant biliary stenoses.

Differentiating malignant from nonmalignant biliary stenoses is challenging. This could be facilitated by the measurement of cancer biomarkers in bile. We aimed at (i) identifying new cancer biomarkers by comparative proteomic analysis of bile collected from patients with a malignant or benign biliary stenosis (exploratory phase) and (ii) verifying the accuracy of the newly identified potential biomarkers for discriminating malignant versus nonmalignant biliary stenoses in a larger group of patients (confirmation phase). Overall, 66 proteins were found overexpressed (ratio>1.5) in at least one cancer condition using proteomic analysis and 7 proteins were increased in all malignant/nonmalignant disease comparisons. Preliminary screening by immunoblot highlighted carcinoembryonic cell adhesion molecule 6 (CEAM6), a cell surface protein overexpressed in many human cancers, as an interesting candidate biomarker. ELISA subsequently confirmed CEAM6 as a potential bile biomarker for distinguishing malignant from benign biliary stenoses with a receiver operating characteristic (ROC) area under the curve (AUC) of 0.92 (specificity 83%, sensitivity 93%, positive predictive value 93%, and negative predictive value 83%). No significant difference in serum CEAM6 level was found between malignant and nonmalignant samples. Combining bile CEAM6 and serum CA19-9 in a panel further improved diagnostic accuracy for malignant stenoses (AUC 0.96, specificity 83%, sensitivity 97%, positive predictive value 93%, and negative predictive value 91%). CEAM6 measurement in bile could be clinically useful to discriminate between malignant and nonmalignant causes of biliary stenosis. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.

Proteomic approach to investigate pathogenicity and metabolism of methicillin-resistant Staphylococcus aureus.

Over the last two decades, numerous genomes of pathogenic bacteria have been fully sequenced and annotated, while others are continuously being sequenced. To date, the sequences of more than 8,500 whole bacterial genomes are publicly available for research purposes. These efforts in high-throughput sequencing simultaneously to progresses in methods allowing to study whole transcriptome and proteome of bacteria provide the basis of comprehensive understanding of metabolism, adaptability to environment, regulation, resistance pathways, or pathogenicity mechanisms of bacterial pathogens. Staphylococcus aureus is a Gram-positive human pathogen causing a wide variety of infections ranging from benign skin infection to life-threatening diseases. Furthermore, the spreading of multidrug-resistant isolates requiring the use of last barrier drugs has resulted in a particular attention of the medical and scientific community to this pathogen. We describe here proteomic methods to prepare, identify, and analyze protein fractions, which allow studying Staphylococcus aureus on the organism level. Besides evaluation of the whole bacterial transcriptome, this approach might contribute to the development of rapid diagnostic tests and to the identification of new drug targets to improve public health.

Cerebrospinal fluid interleukin-6 in central nervous system inflammatory diseases.

BACKGROUND: Interleukin (IL)-6 is recognised as an important cytokine involved in inflammatory diseases of the central nervous system (CNS). OBJECTIVE: To perform a large retrospective study designed to test cerebrospinal fluid (CSF) IL-6 levels in the context of neurological diseases, and evaluate its usefulness as a biomarker to help discriminate multiple sclerosis (MS) from other inflammatory neurological diseases (OIND). PATIENTS AND METHODS: We analyzed 374 CSF samples for IL-6 using a quantitative enzyme-linked immunosorbent assay. Groups tested were composed of demyelinating diseases of the CNS (DD, n = 117), including relapsing-remitting MS (RRMS, n = 65), primary progressive MS (PPMS, n = 11), clinically isolated syndrome (CIS, n = 11), optic neuritis (ON, n = 30); idiopathic transverse myelitis (ITM, n = 10); other inflammatory neurological diseases (OIND, n = 35); and non-inflammatory neurological diseases (NIND, n = 212). Differences between groups were analysed using Kruskal-Wallis test and Mann-Whitney U-test. RESULTS: CSF IL-6 levels exceeded the positivity cut-off of 10 pg/ml in 18 (51.4%) of the 35 OIND samples, but in only three (3.9%) of the 76 MS samples collected. CSF IL-6 was negative for all NIND samples tested (0/212). IL-6 cut-off of 10 pg/ml offers 96% sensitivity to exclude MS. CONCLUSION: CSF IL-6 may help to differentiate MS from its major differential diagnosis group, OIND.

Quantitative mass spectrometry analysis of intact hemoglobin A2 by precursor ion isolation and detection.

Precise and accurate quantification of proteins is essential in clinical laboratories. Here, we present a mass spectrometry (MS)-based method for the quantification of intact proteins in an ion trap mass spectrometer. The developed method is based on the isolation and detection of precursor ions for the quantification of the corresponding signals. The method was applied for the quantification of hemoglobin (Hb) A2, a marker used for the diagnosis of a ß-thalassemia trait. The α and δ globin chains, corresponding to total Hb and HbA2, respectively, were isolated in the ion trap at specific charge states and ejected without activation. Areas of the corresponding isolated precursor ions were used to calculate the δ to α ratio. Three series of quantifications were performed on 7 different days. The standard curve fitted linearly (R(2) = 0.9982) and allowed quantification of HbA2 over a concentration range from 3% to 18% of total Hb. Analytical imprecision ranged from 3.5% to 5.3%, which is enough to determine if the HbA2 level is below 3.5% or above 3.7%. In conclusion, our method reaches precision requirements that would be acceptable for the quantitative measurement of diagnostic proteins, such as HbA2, in clinical laboratories.

Time-course proteomic analysis of taurocholate-induced necrotizing acute pancreatitis.

Acute pancreatitis is an inflammatory disease of the pancreas, which varies greatly in course and severity. Severe forms are associated with serious local and/or systemic complications, and eventually death. The pathobiology of acute pancreatitis is complex. Animal models have been developed to investigate pathobiological processes and identify factors determining disease course. We performed a time-course proteomic analysis using a rat model of severe necrotizing acute pancreatitis induced by taurocholate perfusion in the pancreatic ducts. Results showed that levels of proteins associated to a given biological process changed in a coordinated fashion after disease onset. It was possible to follow the response of a particular pathobiological process to pancreatitis induction and to compare the course of protein pathways. Proteins involved in acinar cell secretion were found to follow a different kinetics than other cellular processes. After an initial decrease, secretory pathway-associated proteins raised again at 18 h post-induction. This phenomenon coincided with a burst in the expression of pancreatitis-associated protein (REG3A), an acute phase protein produced by the exocrine pancreas, and with the decrease of classical markers of pancreatic injury, suggesting that the expression of proteins associated to the secretory pathway may be a modulating factor of pancreas injury. BIOLOGICAL SIGNIFICANCE: Acute pancreatitis (AP) is a complex inflammatory disease, the pathobiology of which is not yet fully understood. Various animal models, relying on different mechanisms of disease induction, have been developed in order to investigate pathobiological processes of AP. In this study, we performed a time-course proteomic analysis to investigate changes of the pancreas proteome occurring in an experimental model of AP induced by perfusion of taurocholate, a bile acid, into the pancreatic duct. This experimental model is characterized by a severe disease with pancreatic necrosis and systemic inflammation. The objectives of this study were to determine the kinetics of functionally related proteins in the early steps of the experimental disease in order to identify protein pathways playing key roles in AP pathobiology and to correlate these data with parameters classically used to assess disease severity. The present work provides for the first time an overview of protein expression in the pancreas during the course of taurocholate-induced necrotizing AP. We believe that correlation of these results with data obtained using proteomic or biochemical approaches in various experimental models of AP will help in highlighting new features, generating hypotheses and constitute therefore a strong and reliable basis for further targeted investigations.

Proteomic analysis of podocyte exosome-enriched fraction from normal human urine.

Urine results from a coordinated activity of glomerular and tubular compartments of the kidney. As a footprint of these cellular functional processes, urinary exosomes, and 40-80 nm membrane vesicles released after fusion with the plasma membrane into the extracellular environment by renal epithelial cells, are a source for identification of proteins and investigation of their role in the kidney. The aim of the present study was the identification of podocyte exosome proteins based on urine immunoabsorption using podocyte-specific CR1-immunocoated beads followed by proteomic analysis using LC MS/MS techniques. This methodology allowed the identification of 1195 proteins. By using a bioinformatic approach, 27 brain-expressed proteins were identified, in which 14 out of them were newly demonstrated to be expressed in the kidney at a mRNA level, and, one of them, the COMT protein, was demonstrated to be expressed in podocytes at a protein level. These results, attesting the reliability of the methodology to identify podocyte proteins, need now to be completed by further experiments to analyze more precisely their biological function(s) in the podocytes.

EasyProt--an easy-to-use graphical platform for proteomics data analysis.

High throughput protein identification and quantification analysis based on mass spectrometry are fundamental steps in most proteomics projects. Here, we present EasyProt (available at http://easyprot.unige.ch), a new platform for mass spectrometry data processing, protein identification, quantification and unexpected post-translational modification characterization. EasyProt provides a fully integrated graphical experience to perform a large part of the proteomic data analysis workflow. Our goal was to develop a software platform that would fulfill the needs of scientists in the field, while emphasizing ease-of-use for non-bioinformatician users. Protein identification is based on OLAV scoring schemes and protein quantification is implemented for both, isobaric labeling and label-free methods. Additional features are available, such as peak list processing, isotopic correction, spectra filtering, charge-state deconvolution and spectra merging. To illustrate the EasyProt platform, we present two identification and quantification workflows based on isobaric tagging and label-free methods.

Quantitative Clinical Chemistry Proteomics (qCCP) using mass spectrometry: general characteristics and application.

Proteomics studies typically aim to exhaustively detect peptides/proteins in a given biological sample. Over the past decade, the number of publications using proteomics methodologies has exploded. This was made possible due to the availability of high-quality genomic data and many technological advances in the fields of microfluidics and mass spectrometry. Proteomics in biomedical research was initially used in 'functional' studies for the identification of proteins involved in pathophysiological processes, complexes and networks. Improved sensitivity of instrumentation facilitated the analysis of even more complex sample types, including human biological fluids. It is at that point the field of clinical proteomics was born, and its fundamental aim was the discovery and (ideally) validation of biomarkers for the diagnosis, prognosis, or therapeutic monitoring of disease. Eventually, it was recognized that the technologies used in clinical proteomics studies [particularly liquid chromatography-tandem mass spectrometry (LC-MS/MS)] could represent an alternative to classical immunochemical assays. Prior to deploying MS in the measurement of peptides/proteins in the clinical laboratory, it seems likely that traditional proteomics workflows and data management systems will need to adapt to the clinical environment and meet in vitro diagnostic (IVD) regulatory constraints. This defines a new field, as reviewed in this article, that we have termed quantitative Clinical Chemistry Proteomics (qCCP).