Pseudomonas aeruginosa infections are prevented in cystic fibrosis patients by avian antibodies binding Pseudomonas aeruginosa flagellin

Pseudomonas aeruginosa (PA) is the main cause of morbidity and mortality in cystic fibrosis (CF) patients. CF patients with chronic PA infections have a more rapid deterioration of their lung function and the bacteria become impossible to eradicate from the lungs. Antibiotic resistance among PA strains in CF patients is steadily increasing. Specific chicken (IgY) antibodies against PA have been shown to have potential to prevent PA infections in CF. Anti-Pseudomonas IgY reduces PA adhesion to epithelia, but the mechanism has not been fully elucidated. To gain further insight into the prophylactic effect of these antibodies, the immunoreactivity was investigated by 2D electrophoresis of PA strains, immunoblotting and MALDI-TOF-MS. To confirm the identity of the proteins, the tryptic peptides were analyzed by MALDI-TOF-MS to accurately measure their monoisotopic masses as well as determine their amino acid sequences. In order to facilitate fragmentation of the peptides they were N-terminally or C-terminally labeled. Several strains were investigated and anti-Pseudomonas IgY was immunoreactive against all of these strains, which strengthens its potential as a prophylactic treatment against PA. Flagellin was identified as the major antigen. Flagellin is the main protein of the flagella and is crucial for establishing infections in hosts as well as being involved in PA chemotaxis, motility, adhesion and inflammation. Furthermore, secreted flagellin elicits an inflammatory response. In conclusion, anti-Pseudomonas IgY binds flagellin, which may prevent PA infections in CF patients by hindering host invasion.     

The sentinel within: exploiting the immune system for cancer biomarkers

The release of proteins from tumors triggers an immune response in cancer patients. These tumor antigens arise from several mechanisms including tumor-specific alterations in protein expression, mutation, folding, degradation, or intracellular localization. Responses to most tumor antigens are rarely observed in healthy individuals, making the response itself a biomarker that betrays the presence of underlying cancer. Antibody immune responses show promise as clinical biomarkers because antibodies have long half-lives in serum, are easy to measure, and are stable in blood samples. However, our understanding of the specificity and the impact of the immune response in early stages of cancer is limited. The immune response to cancer, whether endogenous or driven by vaccines, involves highly specific T lymphocytes (which target tumor-derived peptides bound to self-MHC proteins) and B lymphocytes (which generate antibodies to tumor-derived proteins). T cell target antigens have been identified either by expression cloning from tumor cDNA libraries, or by prediction based on patterns of antigen expression ("reverse immunology"). B cell targets have been similarly identified using the antibodies in patient sera to screen cDNA libraries derived from tumor cell lines. This review focuses on the application of recent advances in proteomics for the identification of tumor antigens. These advances are opening the door for targeted vaccine development, and for using immune response signatures as biomarkers for cancer diagnosis and monitoring.     

Antibodies isolated by using cloned surface antigens recognize antigenically related components of Legionella pneumophila and other Legionella species

We studied the antigenic cross-reactivity of surface proteins among various strains of Legionella pneumophila and other Legionella species by using a novel method of antibody purification. Anti-bacterial antibodies in hyperimmune sera were adsorbed to and eluted from the surface of recombinant E. coli cells that express individual L. pneumophila antigens on their surface. These affinity-purified antibodies were then used to probe protein immunoblots prepared from the test strains to detect cross-reactive domains. We found that antigenic proteins are generally conserved in all L. pneumophila serogroups. Although some of these antigenic domains are shared with members of other Legionella species, they are associated with proteins of different molecular mass. Our approach to the study of antigenic cross-reactivity has potential advantages over similar studies that use either monoclonal antibodies or monospecific antibodies prepared by immunization with purified antigens.     

Identification of proteins of potential diagnostic value for bovine paratuberculosis

Previously we showed that Mycobacterium paratuberculosis culture filtrates (CFs) contain more antigens that react with sera from infected cattle than do cellular extracts of the organism. The goal of the present study was to identify proteins of potential diagnostic value among these CF proteins. Proteins of potential interest were first separated by 2-DE. Roughly 240 CF protein spots were detected on CBB-stained gels using Phoretix 2D software. Of these, 83% reacted with serum from M. paratuberculosis-infected cattle in immunoblots. When bovine serum was absorbed with M. phlei antigens, however, only 37 of these antigenic protein spots were reactive. Twenty-four of these spots were selected for identification based on their immunoblot staining intensity and differences in pI and mass. A total of 14 proteins were ultimately identified by MS and BLAST searches as ModD, PepA, ArgJ, CobT, Antigen 85C, and nine hypothetical proteins. N-terminal peptide analysis of PepA, Antigen 85C, ModD, MAP1693c, MAP2168c, and MAP1022c showed that each protein has 27-39 amino acids that may function as a signal sequence suggesting they are secreted through a Sec-dependent pathway. These 14 proteins from M. paratuberculosis CF are strong candidates for use as antigens for improved serodiagnostic tests for bovine paratuberculosis.     

Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer

Despite their potential to impact diagnosis and treatment of cancer, few protein biomarkers are in clinical use. Biomarker discovery is plagued with difficulties ranging from technological (inability to globally interrogate proteomes) to biological (genetic and environmental differences among patients and their tumors). We urgently need paradigms for biomarker discovery. To minimize biological variation and facilitate testing of proteomic approaches, we employed a mouse model of breast cancer. Specifically, we performed LC-MS/MS of tumor and normal mammary tissue from a conditional HER2/Neu-driven mouse model of breast cancer, identifying 6758 peptides representing >700 proteins. We developed a novel statistical approach (SASPECT) for prioritizing proteins differentially represented in LC-MS/MS datasets and identified proteins over- or under-represented in tumors. Using a combination of antibody-based approaches and multiple reaction monitoring-mass spectrometry (MRM-MS), we confirmed the overproduction of multiple proteins at the tissue level, identified fibulin-2 as a plasma biomarker, and extensively characterized osteopontin as a plasma biomarker capable of early disease detection in the mouse. Our results show that a staged pipeline employing shotgun-based comparative proteomics for biomarker discovery and multiple reaction monitoring for confirmation of biomarker candidates is capable of finding novel tissue and plasma biomarkers in a mouse model of breast cancer. Furthermore, the approach can be extended to find biomarkers relevant to human disease.     

Glucopeptides derived from myelin-relevant proteins and hyperglucosylated nontypeable Haemophilus influenzae bacterial adhesin cross-react with multiple sclerosis specific antibodies: A step forward in the identification of native autoantigens in multiple sclerosis

Multiple sclerosis (MS) is an inflammatory and autoimmune disorder, in which an antibody-mediated demyelination mechanism plays a critical role. We prepared two glucosylated peptides derived from the human myelin proteins, that is, oligodendrocyte-myelin glycoprotein (OMGp) and reticulon-4 receptor (RTN4R), selected by a bioinformatic approach for their conformational homology with CSF114(Glc), a designed β-turn antigenic probe derived from myelin oligodendrocyte glycoprotein (MOG), a glycoprotein present in the CNS. This synthetic antigen is specifically recognized by antibodies in sera of MS patients. We report herein the antigenic properties of these peptides, showing, on the one hand, that MS patient antibodies recognize the two glucosylated peptides and, on the other hand, that these antibodies cross-react with CSF114(Glc) and with the previously described hyperglucosylated nontypeable Haemophilus influenzae bacterial adhesin protein HMW1ct(Glc). These observations point to an immunological association between human and bacterial protein antigens, underpinning the hypothesis that molecular mimicry triggers the breakdown of self-tolerance in MS and suggesting that RTN4R and OMGp can be considered as autoantigens.     

A Method for Producing Protein Nanoparticles with Applications in Vaccines

A practical method is described for synthesizing conjugated protein nanoparticles using thioether (thiol-maleimide) cross-linking chemistry. This method fills the need for a reliable and reproducible synthesis of protein conjugate vaccines for preclinical studies, which can be adapted to produce comparable material for clinical studies. The described method appears to be generally applicable to the production of nanoparticles from a variety of soluble proteins having different structural features. Examples presented include single-component particles of the malarial antigens AMA1, CSP and Pfs25, and two component particles comprised of those antigens covalently cross-linked with the immunogenic carrier protein EPA (a detoxified form of exotoxin A from Pseudomonas aeruginosa). The average molar masses (Mw) of particles in the different preparations ranged from 487 kDa to 3,420 kDa, with hydrodynamic radii (Rh) ranging from 12.1 nm to 38.3 nm. The antigenic properties and secondary structures of the proteins within the particles appear to be largely intact, with no significant changes seen in their far UV circular dichroism spectra, or in their ability to bind conformation-dependent monoclonal antibodies. Mice vaccinated with mixed particles of Pfs25 or CSP and EPA generated significantly greater antigen-specific antibody levels compared with mice vaccinated with the respective unmodified monomeric antigens, validating the potential of antigen-EPA nanoparticles as vaccines.     

Autoantibodies in cancer: prognostic biomarkers and immune activation

The development of proteomic technologies that display a wide variety of antigenic structures has led to the identification of autoantibodies to cancer-derived tumor antigens. These autoantibodies have been detected in sera from patients with multiple cancer types, and are being evaluated as biomarkers for early cancer detection. It is not known whether these antibodies also contribute to active immune surveillance or even tumorigenicity of developing tumors. Here, we review which tumor antigen-specific antibodies are prognostic biomarkers of cancer outcome, and emerging proteomic methods for the isolation and cloning of these antibodies for potential molecular diagnostics and therapeutics.     

Autoantibodies in cancer: prognostic biomarkers and immune activation

The development of proteomic technologies that display a wide variety of antigenic structures has led to the identification of autoantibodies to cancer-derived tumor antigens. These autoantibodies have been detected in sera from patients with multiple cancer types, and are being evaluated as biomarkers for early cancer detection. It is not known whether these antibodies also contribute to active immune surveillance or even tumorigenicity of developing tumors. Here, we review which tumor antigen-specific antibodies are prognostic biomarkers of cancer outcome, and emerging proteomic methods for the isolation and cloning of these antibodies for potential molecular diagnostics and therapeutics.     

Proteomic profiling of cerebrospinal fluid identifies biomarkers for amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is characterized by degeneration of motor neurons. We tested the hypothesis that proteomic analysis will identify protein biomarkers that provide insight into disease pathogenesis and are diagnostically useful. To identify ALS specific biomarkers, we compared the proteomic profile of cerebrospinal fluid (CSF) from ALS and control subjects using surface-enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF-MS). We identified 30 mass ion peaks with statistically significant (p < 0.01) differences between control and ALS subjects. Initial analysis with a rule-learning algorithm yielded biomarker panels with diagnostic predictive value as subsequently assessed using an independent set of coded test subjects. Three biomarkers were identified that are either decreased (transthyretin, cystatin C) or increased (carboxy-terminal fragment of neuroendocrine protein 7B2) in ALS CSF. We validated the SELDI-TOF-MS results for transthyretin and cystatin C by immunoblot and immunohistochemistry using commercially available antibodies. These findings identify a panel of CSF protein biomarkers for ALS.     

Ribosome display: next-generation display technologies for production of antibodies in vitro

Antibodies represent an important and growing class of biologic research reagents and biopharmaceutical products. They can be used as therapeutics in a variety of diseases. With the rapid expansion of proteomic studies and biomarker discovery, there is a need for the generation of highly specific binding reagents to study the vast number of proteins encoded by the genome. Display technologies provide powerful tools for obtaining antibodies. Aside from the preservation of natural antibody repertoires, they are capable of exploiting diversity by DNA recombination to create very large libraries for selection of novel molecules. In contrast to in vivo immunization processes, display technologies allow selection of antibodies under in vitro-defined selection condition(s), resulting in enrichment of antibodies with desired properties from large populations. In addition, in vitro selection enables the isolation of antibodies against difficult antigens including self-antigens, and this can be applied to the generation of human antibodies against human targets. Display technologies can also be combined with DNA mutagenesis for antibody evolution in vitro. Some methods are amenable to automation, permitting high-throughput generation of antibodies. Ribosome display is considered as representative of the next generation of display technologies since it overcomes the limitations of cell-based display methods by using a cell-free system, offering advantages of screening larger libraries and continuously expanding new diversity during selection. Production of display-derived antibodies can be achieved by choosing one of a variety of prokaryotic and eukaryotic cell-based expression systems. In the near future, cell-free protein synthesis may be developed as an alternative for large-scale generation of antibodies.     

Ribosome display: next-generation display technologies for production of antibodies in vitro

Antibodies represent an important and growing class of biologic research reagents and biopharmaceutical products. They can be used as therapeutics in a variety of diseases. With the rapid expansion of proteomic studies and biomarker discovery, there is a need for the generation of highly specific binding reagents to study the vast number of proteins encoded by the genome. Display technologies provide powerful tools for obtaining antibodies. Aside from the preservation of natural antibody repertoires, they are capable of exploiting diversity by DNA recombination to create very large libraries for selection of novel molecules. In contrast to in vivo immunization processes, display technologies allow selection of antibodies under in vitro-defined selection condition(s), resulting in enrichment of antibodies with desired properties from large populations. In addition, in vitro selection enables the isolation of antibodies against difficult antigens including self-antigens, and this can be applied to the generation of human antibodies against human targets. Display technologies can also be combined with DNA mutagenesis for antibody evolution in vitro. Some methods are amenable to automation, permitting high-throughput generation of antibodies. Ribosome display is considered as representative of the next generation of display technologies since it overcomes the limitations of cell-based display methods by using a cell-free system, offering advantages of screening larger libraries and continuously expanding new diversity during selection. Production of display-derived antibodies can be achieved by choosing one of a variety of prokaryotic and eukaryotic cell-based expression systems. In the near future, cell-free protein synthesis may be developed as an alternative for large-scale generation of antibodies.     

Construction of helper plasmid-mediated dual-display phage for autoantibody screening in serum

M13 filamentous bacteriophage has been used in displaying disease-specific antibodies, biomarkers, and peptides. One of the major drawbacks of using phage in diagnostic assays is the aspecific adsorption of proteins leading to a high background signal and decreasing sensitivity. To deal with this, we developed a genetically pure, exchangeable dual-display phage system in which biomarkers and streptavidin-binding protein (SBP) are displayed at opposite ends of the phage. This approach allows for sample purification, using streptavidin-coated magnetic beads resulting in a higher sensitivity of signal detection assays. Our dual-display cassette system approach also allows for easy exchange of both the anchor protein (SBP) and the displayed biomarker. The presented principle is applied for the detection of antibody reactivity against UH-RA.21 which is a good candidate biomarker for rheumatoid arthritis (RA). The applicability of dual-display phage preparation using a helper plasmid system is demonstrated, and its increased sensitivity in phage ELISA assays using patient serum samples is shown.     

Use of an immunoaffinity-mass spectrometry-based approach for the quantification of protein biomarkers from serum samples of lung cancer patients

It is a challenging task to verify and quantify potential biomarkers expressed at elevated levels in sera from cancer patients. An immunoaffinity-mass spectrometry-based approach has been developed using antibodies to enrich proteins of interest from sera followed by mass spectrometry-based quantification. Antibodies specific to the protein of interest were immobilized to hydrazide resin via the carbohydrate moiety on the Fc region of the antibody. Captured proteins were eluted, reduced, alkylated, and digested with trypsin. Peptides were analyzed by LC coupled with multiple reaction monitoring approach, and quantification was achieved by the addition of stable isotope-labeled (heavy) standard peptides. Using this methodology, we were able to achieve a linear response from 15 to 250 ng/ml for carcinoembryonic antigen (CEA), a known tumor biomarker. Moreover we observed elevated levels of CEA in sera samples from lung cancer patients that to our knowledge is the first time that circulating CEA has been detected by mass spectrometry-based analysis. This approach was further applied to potential protein biomarkers discovered from tumor cell lines and tumor tissues. A linear response was obtained from a multiplex spiking experiment in normal human sera for secretory leukocyte peptidase inhibitor (4-500 ng/ml), tissue factor pathway inhibitor (TFPI) (42-1000 ng/ml), tissue factor pathway inhibitor 2 (TFPI2) (2-250 ng/ml), and metalloproteinase inhibitor 1 (TIMP1) (430-1000 ng/ml). A replicate experiment for a single concentration value yielded a relative coefficient of variation better than 11% for TFPI, secretory leukocyte peptidase inhibitor, and TFPI2. The expression level of the proteins in lung cancer patient sera was assayed by an immunoaffinity-multiple reaction monitoring method, and the results were comparable with those obtained from ELISA. This immunoaffinity-mass spectrometry-based quantification approach thus provides a specific and accurate assay for verifying the expression of potential biomarkers in patient serum samples especially for those proteins for which the necessary reagents for ELISA development are unavailable.     

Antibody-based enrichment of peptides on magnetic beads for mass-spectrometry-based quantification of serum biomarkers

A major bottleneck for validation of new clinical diagnostics is the development of highly sensitive and specific assays for quantifying proteins. We previously described a method, stable isotope standards with capture by antipeptide antibodies, wherein a specific tryptic peptide is selected as a stoichiometric representative of the protein from which it is cleaved, is enriched from biological samples using immobilized antibodies, and is quantitated using mass spectrometry against a spiked internal standard to yield a measure of protein concentration. In this study, we optimized a magnetic-bead-based platform amenable to high-throughput peptide capture and demonstrated that antibody capture followed by mass spectrometry can achieve ion signal enhancements on the order of 10(3), with precision (CVs <10%) and accuracy (relative error approximately 20%) sufficient for quantifying biomarkers in the physiologically relevant ng/mL range. These methods are generally applicable to any protein or biological fluid of interest and hold great potential for providing a desperately needed bridging technology between biomarker discovery and clinical application.     

Secreted proteins as a fundamental source for biomarker discovery

The proteins secreted by various cells (the secretomes) are a potential rich source of biomarkers as they reflect various states of the cells at real time and at given conditions. To have accessible, sufficient and reliable protein markers is desirable as they mark various stages of disease development and their presence/absence can be used for diagnosis, prognosis, risk stratification and therapeutic monitoring. As direct analysis of blood/plasma, a common and noninvasive patient screening method, can be difficult for candidate protein biomarker identification, the alternative/complementary approaches are required, one of them is the analysis of secretomes in cell conditioned media in vitro. As the proteins secreted by cells as a response to various stimuli are most likely secreted into blood/plasma, the identification and pre-selection of candidate protein biomarkers from cell secretomes with subsequent validation of their presence at higher levels in serum/plasma is a promising approach. In this review, we discuss the proteins secreted by three progenitor cell types (smooth muscle, endothelial and cardiac progenitor cells) and two adult cell types (neonatal rat ventrical myocytes and smooth muscle cells) which can be relevant to cardiovascular research and which have been recently published in the literature. We found, at least for secretome studies included in this review, that secretomes of progenitor and adult cells overlap by 48% but the secretomes are very distinct among progenitor cell themselves as well as between adult cells. In addition, we compared secreted proteins to protein identifications listed in the Human Plasma PeptideAtlas and in two reports with cardiovascular-related proteins and we performed the extensive literature search to find if any of these secreted proteins were identified in a biomarker study. As expected, many proteins have been identified as biomarkers in cancer but 18 proteins (out of 62) have been tested as biomarkers in cardiovascular diseases as well.     

A lectin-coupled, targeted proteomic mass spectrometry (MRM MS) platform for identification of multiple liver cancer biomarkers in human plasma

Aberrantly glycosylated proteins related to liver cancer progression were captured with specific lectin and identified from human plasma by multiple reaction monitoring (MRM) mass spectrometry as multiple biomarkers for hepatocellular carcinoma (HCC). The lectin fractionation for fucosylated protein glycoforms in human plasma was conducted with a fucose-specific aleuria aurantia lectin (AAL). Following tryptic digestion of the lectin-captured fraction, plasma samples from 30 control cases (including 10 healthy, 10 hepatitis B virus [HBV], and 10 cirrhosis cases) and 10 HCC cases were quantitatively analyzed by MRM to identify which glycoproteins are viable HCC biomarkers. A1AG1, AACT, A1AT, and CERU were found to be potent biomarkers to differentiate HCC plasma from control plasmas. The AUROC generated independently from these four biomarker candidates ranged from 0.73 to 0.92. However, the lectin-coupled MRM assay with multiple combinations of biomarker candidates is superior statistically to those generated from the individual candidates with AUROC more than 0.95, which can be an alternative to the immunoassay inevitably requiring tedious development of multiple antibodies against biomarker candidates to be verified. Eventually the lectin-coupled, targeted proteomic mass spectrometry (MRM MS) platform was found to be efficient to identify multiple biomarkers from human plasma according to cancer progression.     

The knowledge-integrated network biomarkers discovery for major adverse cardiac events

The mass spectrometry (MS) technology in clinical proteomics is very promising for discovery of new biomarkers for diseases management. To overcome the obstacles of data noises in MS analysis, we proposed a new approach of knowledge-integrated biomarker discovery using data from Major Adverse Cardiac Events (MACE) patients. We first built up a cardiovascular-related network based on protein information coming from protein annotations in Uniprot, protein-protein interaction (PPI), and signal transduction database. Distinct from the previous machine learning methods in MS data processing, we then used statistical methods to discover biomarkers in cardiovascular-related network. Through the tradeoff between known protein information and data noises in mass spectrometry data, we finally could firmly identify those high-confident biomarkers. Most importantly, aided by protein-protein interaction network, that is, cardiovascular-related network, we proposed a new type of biomarkers, that is, network biomarkers, composed of a set of proteins and the interactions among them. The candidate network biomarkers can classify the two groups of patients more accurately than current single ones without consideration of biological molecular interaction.     

Cell Surface Profiling Using High-Throughput Flow Cytometry: A Platform for Biomarker Discovery and Analysis of Cellular Heterogeneity

Cell surface proteins have a wide range of biological functions, and are often used as lineage-specific markers. Antibodies that recognize cell surface antigens are widely used as research tools, diagnostic markers, and even therapeutic agents. The ability to obtain broad cell surface protein profiles would thus be of great value in a wide range of fields. There are however currently few available methods for high-throughput analysis of large numbers of cell surface proteins. We describe here a high-throughput flow cytometry (HT-FC) platform for rapid analysis of 363 cell surface antigens. Here we demonstrate that HT-FC provides reproducible results, and use the platform to identify cell surface antigens that are influenced by common cell preparation methods. We show that multiple populations within complex samples such as primary tumors can be simultaneously analyzed by co-staining of cells with lineage-specific antibodies, allowing unprecedented depth of analysis of heterogeneous cell populations. Furthermore, standard informatics methods can be used to visualize, cluster and downsample HT-FC data to reveal novel signatures and biomarkers. We show that the cell surface profile provides sufficient molecular information to classify samples from different cancers and tissue types into biologically relevant clusters using unsupervised hierarchical clustering. Finally, we describe the identification of a candidate lineage marker and its subsequent validation. In summary, HT-FC combines the advantages of a high-throughput screen with a detection method that is sensitive, quantitative, highly reproducible, and allows in-depth analysis of heterogeneous samples. The use of commercially available antibodies means that high quality reagents are immediately available for follow-up studies. HT-FC has a wide range of applications, including biomarker discovery, molecular classification of cancers, or identification of novel lineage specific or stem cell markers.     

Immunochemical characterization of the outer membrane complex of Serratia marcescens and identification of the antigens accessible to antibodies on the cell surface

Serratia marcescens New CDC O14:H12 contains major outer membrane proteins of 43.5 kDal, 42 kDal (the porins) and 38 kDal (the OmpA protein) which can be separated by sodium dodecyl sulphate-polyacrylamide gel electrophoresis. Immunoblotting of whole cell or outer membrane preparations using antiserum raised against the whole cells revealed similar complex patterns of antigens. The OmpA protein was the major immunogen, although six other outer membrane proteins were also detected; the porins reacted only weakly with antibodies in this system. Immunoabsorption of antisera with whole cells showed that only the O antigenic chains of lipopolysaccharide and the H (flagella) antigens were accessible to antibody on the cell surface. Failure to detect the OmpA protein and other envelope antigens in this way suggests that their antigenic sites are not able to react with antibodies and are possibly masked by the O antigen.