11 research outputs found

    Quantitative Proteomic Profiling Reveals Differentially Regulated Proteins in Cystic Fibrosis Cells

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    The most prevalent cause of cystic fibrosis (CF) is the deletion of a phenylalanine residue at position 508 in CFTR (ΔF508-CFTR) protein. The mutated protein fails to fold properly, is retained in the endoplasmic reticulum via the action of molecular chaperones, and is tagged for degradation. In this study, the differences in protein expression levels in CF cell models were assessed using a systems biology approach aided by the sensitivity of MudPIT proteomics. Analysis of the differential proteome modulation without a priori hypotheses has the potential to identify markers that have not yet been documented. These may also serve as the basis for developing new diagnostic and treatment modalities for CF. Several novel differentially expressed proteins observed in our study are likely to play important roles in the pathogenesis of CF and may serve as a useful resource for the CF scientific community

    Quantitative Proteomic Profiling Reveals Differentially Regulated Proteins in Cystic Fibrosis Cells

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    The most prevalent cause of cystic fibrosis (CF) is the deletion of a phenylalanine residue at position 508 in CFTR (ΔF508-CFTR) protein. The mutated protein fails to fold properly, is retained in the endoplasmic reticulum via the action of molecular chaperones, and is tagged for degradation. In this study, the differences in protein expression levels in CF cell models were assessed using a systems biology approach aided by the sensitivity of MudPIT proteomics. Analysis of the differential proteome modulation without a priori hypotheses has the potential to identify markers that have not yet been documented. These may also serve as the basis for developing new diagnostic and treatment modalities for CF. Several novel differentially expressed proteins observed in our study are likely to play important roles in the pathogenesis of CF and may serve as a useful resource for the CF scientific community

    Comparison of Protein Expression Ratios Observed by Sixplex and Duplex TMT Labeling Method

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    Stable isotope labeling via isobaric derivatization of peptides is a universally applicable approach that enables concurrent identification and quantification of proteins in different samples using tandem mass spectrometry. In this study, we evaluated the performance of amine-reactive isobaric tandem mass tag (TMT), available as duplex and sixplex sets, with regard to their ability to elucidate protein expression changes. Using rat brain tissue from two different developmental time points, postnatal day 1 (p1) and 45 (p45), as a model system, we compared the protein expression ratios (p45/p1) observed using duplex TMT tags in triplicate measurements versus sixplex tag in a single LC–MS/MS analysis. A correlation of 0.79 in relative protein abundance was observed in the proteins quantified by these two sets of reagents. However, more proteins passed the criteria for significant fold change (−1.0 ≤ log<sub>2</sub> ratio (p45/p1) ≥ +1.0 and <i>p</i> < 0.05) in the sixplex analysis. Nevertheless, in both methods most proteins showing significant fold change were identified by multiple spectra, increasing their quantification precision. Additionally, the fold change in p45 rats against p1, observed in TMT experiments, was corroborated by a metabolic labeling strategy where relative quantification of differentially expressed proteins was obtained using <sup>15</sup>N-labeled p45 rats as an internal standard

    PSEA-Quant: A Protein Set Enrichment Analysis on Label-Free and Label-Based Protein Quantification Data

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    The majority of large-scale proteomics quantification methods yield long lists of quantified proteins that are often difficult to interpret and poorly reproduced. Computational approaches are required to analyze such intricate quantitative proteomics data sets. We propose a statistical approach to computationally identify protein sets (e.g., Gene Ontology (GO) terms) that are significantly enriched with abundant proteins with reproducible quantification measurements across a set of replicates. To this end, we developed PSEA-Quant, a protein set enrichment analysis algorithm for label-free and label-based protein quantification data sets. It offers an alternative approach to classic GO analyses, models protein annotation biases, and allows the analysis of samples originating from a single condition, unlike analogous approaches such as GSEA and PSEA. We demonstrate that PSEA-Quant produces results complementary to GO analyses. We also show that PSEA-Quant provides valuable information about the biological processes involved in cystic fibrosis using label-free protein quantification of a cell line expressing a CFTR mutant. Finally, PSEA-Quant highlights the differences in the mechanisms taking place in the human, rat, and mouse brain frontal cortices based on tandem mass tag quantification. Our approach, which is available online, will thus improve the analysis of proteomics quantification data sets by providing meaningful biological insights

    Proteomic Analysis of Signaling Network Regulation in Renal Cell Carcinomas with Differential Hypoxia-Inducible Factor-2α Expression

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    <div><p>Background</p><p>The loss of von Hippel–Lindau (<i>VHL</i>) protein function leads to highly vascular renal tumors characterized by an aggressive course of disease and refractoriness to chemotherapy and radiotherapy. Loss of <i>VHL</i> in renal tumors also differs from tumors of other organs in that the oncogenic cascade is mediated by an increase in the levels of hypoxia-inducible factor-2α (HIF2α) instead of hypoxia-inducible factor-1α (HIF1α).</p><p>Methods and Principal Findings</p><p>We used renal carcinoma cell lines that recapitulate the differences between mutant <i>VHL</i> and wild-type <i>VHL</i> genotypes. Utilizing a method relying on extracted peptide intensities as a label-free approach for quantitation by liquid chromatography–mass spectrometry, our proteomics study revealed regulation of key proteins important for cancer cell survival, proliferation and stress-resistance, and implicated differential regulation of signaling networks in <i>VHL</i>-mutant renal cell carcinoma. We also observed upregulation of cellular energy pathway enzymes and the stress-responsive mitochondrial 60-kDa heat shock protein. Finding reliance on glutaminolysis in <i>VHL</i>-mutant renal cell carcinoma was of particular significance, given the generally predominant dependence of tumors on glycolysis. The data have been deposited to the ProteomeXchange with identifier PXD000335.</p><p>Conclusions and Significance</p><p>Pathway analyses provided corroborative evidence for differential regulation of molecular and cellular functions influencing cancer energetics, metabolism and cell proliferation in renal cell carcinoma with distinct <i>VHL</i> genotype. Collectively, the differentially regulated proteome characterized by this study can potentially guide translational research specifically aimed at effective clinical interventions for advanced <i>VHL</i>-mutant, HIF2α-over-expressing tumors.</p></div

    Ingenuity Pathway Analyses (IPA).

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    <p>Proteins with significant differential expression regulate a network of cell-to-cell signaling and interaction, cellular growth and proliferation, as well as cellular development. Red shading: upregulated in <i>VHL</i>-mut RCC; green shading: downregulated in <i>VHL</i>-mut RCC. Protein–protein interactions from the network diagram are represented by single lines and proteins/compounds that regulate another protein are indicated by arrows. Solid or dashed lines indicate direct or indirect interactions, respectively. The various shapes represent different protein functions.</p

    Assessment of cell-survival by MTT assay.

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    <p>The survival of Caki-2 (<i>VHL</i>-wt) and 786-O (<i>VHL</i>-mut) RCC cell lines was assessed after treatment with increasing concentrations of the glutaminolytic inhibitor, aminooxyacetate (AOA) at 24 h (<b>a</b>), 48 h (<b>b</b>) and 72 h (<b>c</b>) and in glutamine-depleted medium (<b>d</b>). <i>VHL</i>-mut 786-O RCC cells were more susceptible to inhibition of glutaminolysis or glutamine depletion at all time-points (* indicates statistically significant difference from <i>VHL</i>-wt control by the <i>t</i>-test, <i>P</i><0.05, n = 4).</p
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