Proteome Science - Latest Articles
Sun Apr 24 04:42:17 EDT 2011
Home: http://www.proteomesci.com
Feed: http://www.proteomesci.com/rss/

Proteomic and immunoproteomic characterization of a DIVA subunit vaccine against Actinobacillus pleuropneumoniae - Background: Protection of pigs by vaccination against Actinobacillus pleuropneumoniae, the causative agent of porcine pleuropneumonia, is hampered by the presence of 15 different serotypes. A DIVA subunit vaccine comprised of detergent-released proteins from A. pleuropneumoniae serotypes 1, 2 and 5 has been developed and shown to protect pigs from clinical symptoms upon homologous and heterologous challenge. This vaccine has not been characterized in-depth so far. Thus we performed i) mass spectrometry in order to identify the exact protein content of the vaccine and ii) cross-serotype 2-D immunoblotting in order to discover cross-reactive antigens. By these approaches we expected to gain results enabling us to argue about the reasons for the efficacy of the analyzed vaccine. Results: We identified 75 different proteins in the vaccine. Using the PSORTb algorithm these proteins were classified according to their cellular localization. Highly enriched proteins are outer membrane-associated lipoproteins like OmlA and TbpB, integral outer membrane proteins like FrpB, TbpA, OmpA1, OmpA2, HgbA and OmpP2, and secreted Apx toxins. The subunit vaccine also contained large amounts of the ApxIVA toxin so far thought to be expressed only during infection. Applying two-dimensional difference gel electrophoresis (2-D DIGE) we showed different isoforms and variations in expression levels of several proteins among the strains used for vaccine production. For detection of cross-reactive antigens we used detergent released proteins of serotype 7. Sera of pigs vaccinated with the detergent-released proteins of serotypes 1, 2, and 5 detected seven different proteins of serotype 7, and convalescent sera of pigs surviving experimental infection with serotype 7 reacted with 13 different proteins of the detergent-released proteins of A. pleuropneumoniae serotypes 1, 2, and 5. Conclusions: A detergent extraction-based subunit vaccine of A. pleuropneumoniae was characterized by mass spectrometry. It contained a large variety of immunogenic and virulence associated proteins, among them the ApxIVA toxin. The identification of differences in expression as well as isoform variation between the serotypes implied the importance of combining proteins of different serotypes for vaccine generation. This finding was supported by immunoblotting showing the induction of cross-reactive antibodies against several surface associated proteins in immunized animals.

Periostin identied as a potential biomarker of prostate cancer by iTRAQ-proteomics analysis of prostate biopsy - Background: Proteomics may help us better understand the changes of multiple proteins involved in oncogenesis and progression of prostate cancer(PCa) and identify more diagnostic and prognostic biomarkers.The aim of this study was to screen biomarkers of PCa by the proteomics analysis using isobaric tags for relative and absolute quantification(iTRAQ). Methods: The patients undergoing prostate biopsies were classified into 3 groups according to pathological results: benign prostate hyperplasia (BPH, n=20), PCa(n=20) and BPH with local prostatic intraepithelial neoplasm(PIN, n=10). Then, all the specimens from these patients were analyzed by iTRAQ and two-dimensional liquid chromatography-tandem mass spectrometry (2DLC-MS/MS). The Gene Ontology(GO) function and the transcription regulation networks of the differentially expressed were analyzed by MetaCore software. Western blotting and Immunohistochemical staining were used to analyze the interest proteins.Result: A total of 760 proteins were identied from 13787 distinct peptides,including two common proteins that enjoy clinical application: prostate specific antigen (PSA) and prostatic acid phosphatase(PAP). Proteins that expressed differentially between PCa and BPH group were further analyzed. Compared with BPH, 20 proteins were signicantly differentially up-regulated (>1.5-fold) while 26 were signicantly down-regulated in PCa(<0.66-fold). In term of GO database, the differentially expressed proteins were divided into 3 categories: cellular component(CC), molecular function (MF) and biological process(BP). The top 5 transcription regulation networks of the differentially expressed proteins were initiated through activation of SP1, p53, YY1, androgen receptor(AR) and c Myc The overexpression of periostin in PCa was verified by western blotting and immunohistochemical staining. Conclusion: Our study indicates that the iTRAQ technology is a new strategy for global proteomics analysis of the tissues of PCa. A signicant up-regulation of periostin in PCa compared to BPH may provide clues for not only a promising biomarker for the prognosis of PCa but also a potential target for therapeutical intervention.

Identification of Apo-A1 as a biomarker for early diagnosis of bladder transitional cell carcinoma - Background: Bladder transitional cell carcinoma (BTCC) is the fourth most frequent neoplasia in men, clinically characterized by high recurrent rates and poor prognosis. Availability of urinary tumor biomarkers represents a convenient alternative for early detection and disease surveillance because of its direct contact with the tumor and sample accessibility. Results: We tested urine samples from healthy volunteers and patients with low malignant or aggressive BTCC to identify potential biomarkers for early detection of BTCC by two-dimensional electrophoresis (2-DE) coupled with mass spectrometry (MS) and bioinformatics analysis. We observed increased expression of five proteins, including fibrinogen (Fb), lactate dehydrogenase B (LDHB), apolipoprotein-A1 (Apo-A1), clusterin (CLU) and haptoglobin (Hp), which were increased in urine samples of patients with low malignant or aggressive bladder cancer. Further analysis of urine samples of aggressive BTCC showed significant increase in Apo-A1 expression compared to low malignant BTCC. Apo-A1 level was measured quantitatively using enzyme-linked immunosorbent assay (ELISA) and was suggested to provide diagnostic utility to distinguish patients with bladder cancer from controls at 18.22 ng/ml, and distinguish patients with low malignant BTCC from patients with aggressive BTCC in two-tie grading system at 29.86 ng/ml respectively. Further validation assay showed that Apo-A1 could be used as a biomarker to diagnosis BTCC with a sensitivity and specificity of 91.6% and 85.7% respectively, and classify BTCC in two-tie grading system with a sensitivity and specificity of 83.7% and 89.7% respectively. Conclusion: Taken together, our findings suggest Apo-A1 could be a potential biomarker related with early diagnosis and classification in two-tie grading system for bladder cancer.

Improving Detection Accuracy of Lung Cancer Serum Proteomic Profiling via Two-Stage Training Process - Background: Surface-Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI-TOF-MS) is a frequently used technique for cancer biomarker research. The specificity of biomarkers detected by SELDI can be influenced by concomitant inflammation. This study aimed to increase detection accuracy using a two-stage analysis process. Methods: Sera from 118 lung cancer patients, 72 healthy individuals, and 31 patients with inflammatory disease were randomly divided into training and testing groups by 3:2 ratio. In the training group, the traditional method of using SELDI profile analysis to directly distinguish lung cancer patients from sera was used. The two-stage analysis of distinguishing the healthy people and non-healthy patients (1st-stage) and then differentiating cancer patients from inflammatory disease patients (2nd-stage) to minimize the influence of inflammation was validated in the test group. Results: In the test group, the one-stage method had 87.2% sensitivity, 37.5% specificity, and 64.4% accuracy. The two-stage method had lower sensitivity (>70.1%) but statistically higher specificity (80%) and accuracy (74.7%). The predominantly expressed protein peak at 11480 Da was the primary splitter regardless of one- or two-stage analysis. This peak was suspected to be SAA (Serum Amyloid A) due to the similar m/z countered around this area. This hypothesis was further tested using an SAA ELISA assay. Conclusions: Inflammatory disease can severely interfere with the detection accuracy of SELDI profiles for lung cancer. Using a two-stage training process will improve the specificity and accuracy of detecting lung cancer.

Targeted Quantitative Mass Spectrometric Immunoassay for Human Protein Variants - Background: Post-translational modifications and genetic variations give rise to protein variants that significantly increase the complexity of the human proteome. Modified proteins also play an important role in biological processes. While sandwich immunoassays are routinely used to determine protein concentrations, they are oblivious to protein variants that may serve as biomarkers with better sensitivity and specificity than their wild-type proteins. Mass spectrometry, coupled to immunoaffinity separations, can provide an efficient mean for simultaneous detection and quantification of protein variants. Results: Presented here is a mass spectrometric immunoassay method for targeted quantitative proteomics analysis of protein modifications. Cystatin C, a cysteine proteinase inhibitor and a potential marker for several pathological processes, was used as a target analyte. An internal reference standard was incorporated into the assay, serving as a normalization point for cystatin C quantification. The precision, linearity, and recovery characteristics of the assay were established. The new assay was also benchmarked against existing cystatin C ELISA. In application, the assay was utilized to determine the individual concentration of several cystatin C variants across a cohort of samples, demonstrating the ability to fully quantify individual forms of post-translationally modified proteins. Conclusions: The mass spectrometric immunoassays can find use in quantifying specific protein modifications, either as a part of a specific protein biomarker discovery/rediscovery effort to delineate the role of these variants in the onset of the disease, progression, and response to therapy, or in a more systematic study to delineate and understand human protein diversity.

Deglycosylation and label-free quantitative LC-MALDI MS applied to efficient serum biomarker discovery of lung cancer - Background: Serum is an ideal source of biomarker discovery and proteomic profiling studies are continuously pursued on serum samples. However, serum is featured by high level of protein glycosylations that often cause ionization suppression and confound accurate quantification analysis by mass spectrometry. Here we investigated the effect of N-glycan and sialic acid removal from serum proteins on the performance of label-free quantification results. Results: Serum tryptic digests with or without deglycosylation treatment were analyzed by LC-MALDI MS and quantitatively compared on the Expressionist Refiner MS module. As a result, 345 out of 2,984 peaks (11.6 %) showed the specific detection or the significantly improved intensities in deglycosylated serum samples (P < 0.01). We then applied this deglycosylation-based sample preparation to the identification of lung cancer biomarkers. In comparison between 10 healthy controls and 20 lung cancer patients, 40 peptides were identified to be differentially presented (P < 0.01). Their quantitative accuracies were further verified by multiple reaction monitoring. The result showed that deglycosylation was needed for the identification of some unique candidates, including previously unreported O-linked glycopeptide of complement component C9. Conclusions: We demonstrated here that sample deglycosylation improves the quantitative performance of shotgun proteomics, which can be effectively applied to any samples with high glycoprotein contents.

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.

Differential analysis of glioblastoma multiforme proteome by a 2D-DIGE approach - Background: Genomics, transcriptomics and proteomics of glioblastoma multiforme (GBM) have recently emerged as possible tools to discover therapeutic targets and biomarkers for new therapies including immunotherapy. It is well known that macroscopically complete surgical excision, radiotherapy and chemotherapy have therapeutic limitations to improve survival in these patients. In this study, we used a differential proteomic-based technique (2D-Difference Gel Electrophoresis) coupled with matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry to identify proteins that may serve as brain tumor antigens in new therapeutic assays. Five samples of patients presenting a GBM and five samples of microscopically normal brain tissues derived from brain epileptic surgery specimen were labeled and run in 2D-PAGE (Two-Dimensional Polyacrylamide Gel Electrophoresis) with an internal pool sample on each gel. Five gels were matched and compared with DIA (Difference In-gel Analysis) software. Differential spots were picked, in-gel digested and peptide mass fingerprints were obtained. Results: From 51 protein-spots significantly up-regulated in GBM samples, mass spectrometry (MS) identified twenty-two proteins. The differential expression of a selected protein set was first validated by western-blotting, then tested on large cohorts of GBM specimens and non-tumor tissues, using immunohistochemistry and real-time RT-PCR. Conclusions: Our results confirmed the importance of previously described proteins in glioma pathology and their potential usefulness as biological markers but also revealed some new interesting targets for future therapies.

Systems analysis of endothelial cell plasma membrane proteome of rat lung microvasculature - Background: Endothelial cells line all blood vessels to form the blood-tissue interface which is critical for maintaining organ homeostasis and facilitates molecular exchange. We recently used tissue subcellular fractionation combined with several multi-dimensional mass spectrometry-based techniques to enhance identification of lipid-embedded proteins for large-scale proteomic mapping of luminal endothelial cell plasma membranes isolated directly from rat lungs in vivo. The biological processes and functions of the proteins expressed at this important blood-tissue interface remain unexplored at a large scale. Results: We performed an unbiased systems analysis of the endothelial cell surface proteome containing over 1800 proteins to unravel the major functions and pathways apparent at this interface. As expected, many key functions of plasma membranes in general (i.e., cell surface signaling pathways, cytoskeletal organization, adhesion, membrane trafficking, metabolism, mechanotransduction, membrane fusion, and vesicle-mediated transport) and endothelial cells in particular (i.e., blood vessel development and maturation, angiogenesis, regulation of endothelial cell proliferation, protease activity, and endocytosis) were significantly overrepresented in this proteome. We found that endothelial cells express multiple proteins that mediate processes previously reported to be restricted to neuronal cells, such as neuronal survival and plasticity, axon growth and regeneration, synaptic vesicle trafficking and neurotransmitter metabolic process. Surprisingly, molecular machinery for protein synthesis was also detected as overrepresented, suggesting that endothelial cells, like neurons, can synthesize proteins locally at the cell surface. Conclusion: Our unbiased systems analysis has led to the potential discovery of unexpected functions in normal endothelium. The discovery of the existence of protein synthesis at the plasma membrane in endothelial cells provides new insight into the blood-tissue interface and endothelial cell surface biology.

Correction: A comparison of imputation procedures and statistical tests for the analysis of two-dimensional electrophoresis data - The list of authors of this article [Miecznikowski JC, Damodaran S, Sellers KF, Rabin RA: A comparison of imputation procedures and statistical tests for the analysis of two-dimensional electrophoresis data. Proteome Science 2010, 8:66] was incorrect as published and should be as follows: Jeffrey C Miecznikowski, Senthilkumar Damodaran, Kimberly F Sellers, Donald E Coling, Richard Salvi, Richard A RabinCo-authors Donald E Coling and Richard Salvi were omitted in error from the published author list.JCM designed the study, performed the statistical analysis, and wrote the manuscript. SD designed the study, performed the data analysis, and wrote the manuscript. KFS assisted in the statistical analysis and the writing of the manuscript. DEC and RS provided the datasets for analysis. RAR provided the materials and contributed to the conception of the study. All authors read and approved the final manuscript.