10 research outputs found

    Multiplexed, Proteome-Wide Protein Expression Profiling: Yeast Deubiquitylating Enzyme Knockout Strains

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    Characterizing a protein’s function often requires a description of the cellular state in its absence. Multiplexing in mass spectrometry-based proteomics has now achieved the ability to globally measure protein expression levels in yeast from 10 cell states simultaneously. We applied this approach to quantify expression differences in wild type and nine deubiquitylating enzyme (DUB) knockout strains with the goal of creating “information networks” that might provide deeper, mechanistic insights into a protein’s biological role. In total, more than 3700 proteins were quantified with high reproducibility across three biological replicates (30 samples in all). DUB mutants demonstrated different proteomics profiles, consistent with distinct roles for each family member. These included differences in total ubiquitin levels and specific chain linkages. Moreover, specific expression changes suggested novel functions for several DUB family members. For instance, the <i>ubp3Δ</i> mutant showed large expression changes for members of the cytochrome <i>C</i> oxidase complex, consistent with a role for Ubp3 in mitochondrial regulation. Several DUBs also showed broad expression changes for phosphate transporters as well as other components of the inorganic phosphate signaling pathway, suggesting a role for these DUBs in regulating phosphate metabolism. These data highlight the potential of multiplexed proteome-wide analyses for biological investigation and provide a framework for further study of the DUB family. Our methods are readily applicable to the entire collection of yeast deletion mutants and may help facilitate systematic analysis of yeast and other organisms

    Quantitative multiplexed proteomics of <i>Taenia solium</i> cysts obtained from the skeletal muscle and central nervous system of pigs

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    <div><p>In human and porcine cysticercosis caused by the tapeworm <i>Taenia solium</i>, the larval stage (cysts) can infest several tissues including the central nervous system (CNS) and the skeletal muscles (SM). The cyst’s proteomics changes associated with the tissue localization in the host tissues have been poorly studied. Quantitative multiplexed proteomics has the power to evaluate global proteome changes in response to different conditions. Here, using a TMT-multiplexed strategy we identified and quantified over 4,200 proteins in cysts obtained from the SM and CNS of pigs, of which 891 were host proteins. To our knowledge, this is the most extensive intermixing of host and parasite proteins reported for tapeworm infections.Several antigens in cysticercosis, <i>i</i>.<i>e</i>., GP50, paramyosin and a calcium-binding protein were enriched in skeletal muscle cysts. Our results suggested the occurrence of tissue-enriched antigen that could be useful in the improvement of the immunodiagnosis for cysticercosis. Using several algorithms for epitope detection, we selected 42 highly antigenic proteins enriched for each tissue localization of the cysts. Taking into account the fold changes and the antigen/epitope contents, we selected 10 proteins and produced synthetic peptides from the best epitopes. Nine peptides were recognized by serum antibodies of cysticercotic pigs, suggesting that those peptides are antigens. Mixtures of peptides derived from SM and CNS cysts yielded better results than mixtures of peptides derived from a single tissue location, however the identification of the ‘optimal’ tissue-enriched antigens remains to be discovered. Through machine learning technologies, we determined that a reliable immunodiagnostic test for porcine cysticercosis required at least five different antigenic determinants.</p></div

    Peptide mixtures as potential diagnostic agents for <i>Taenia solium</i> cysticercosis.

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    <p>Several peptide mixtures were used: A) The best four individual peptides (using 500 ng or 1 μg to coat each microtiter plate well). The rest of the peptides combinations were used at 500 ng. B) Mixture of all 14 peptides synthesized in this study, C) Mixture of the peptides derived of skeletal muscle (SM) abundant proteins, D) Mixture of one peptide of a central nervous system (CNS) abundant protein and one of a constitutive protein and E) Mixture of peptides from SM and CNS cysts. The normalized optical density was calculated by dividing each individual O.D. by the cut-off value (mean value of non cysticercotic pigs plus two standard deviations). P-values are shown at the top of each figure. F) Heat map showing the individual response to antigenic peptide mixtures. The normalized optical density was transformed using Log<sub>2</sub>. White represents values near to the cut-off point, red represents values over the cut-off point (positive samples) and blue represents values below the cut-off point (negative samples).</p

    <i>k</i>-means clustering and associated biological/molecular functions for proteins of skeletal muscle (SM) and central nervous system (CNS) cysts.

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    <p>Cluster associated with the CNS (A), SM localization (B) and 48 constitutive proteins with the lowest coefficient of variation (C). The proteins included have a P-value <0.01 (n = 261). Only the most frequently observed categories and molecular functions (obtained using Argot2 algorithm) are show on the right panel. The y axis shows the Log<sub>2</sub> (relative abundance).</p

    Protein abundance of several well-studied antigens in <i>T</i>. <i>solium</i> cysts antigens.

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    <p>A) Relative abundance of cyst’s antigens obtained from the skeletal muscle (SM) and central nervous system (CNS); B) Relative abundance of tetraspanin proteins quantified in our proteomic analysis for SM and CNS cysts; C) Alignment of SM- and CNS-abundant tetraspanins. The extracellular loops are bold in red and blue, selected peptides are marked by a square. Listed at the bottom are the selected peptide sequences and length. D) Recognition of the synthetic peptides by non cysticercotic and cysticercotic pig sera. The normalized optical density (O.D.) is the result of dividing each individual O.D. by the cut-off value (mean value of non cysticercotic pigs plus two standard deviations). P-values are shown at the top of each figure.</p

    <i>Taenia solium</i> peptide recognition by cysticercotic and non cysticercotic pig sera through ELISA.

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    <p>A) Peptides from central nervous system, B) skeletal muscle abundant proteins, C) constitutive proteins and D) cysts protein extracts. Microtiter plates were coated with the peptides or extracts and incubated with sera from non cysticercotic (n = 15) and cysticercotic (n = 15) pigs, all bred in rural endemic areas. The normalized optical density (O.D.) is the result of dividing each individual O.D. by the cut-off value (mean value of non cysticercotic pigs plus two standard deviations). P-values are shown at the top of each figure.</p

    Peptide mixtures as potential diagnostic agents for <i>Taenia solium</i> cysticercosis.

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    <p>Several peptide mixtures were used: A) The best four individual peptides (using 500 ng or 1 μg to coat each microtiter plate well). The rest of the peptides combinations were used at 500 ng. B) Mixture of all 14 peptides synthesized in this study, C) Mixture of the peptides derived of skeletal muscle (SM) abundant proteins, D) Mixture of one peptide of a central nervous system (CNS) abundant protein and one of a constitutive protein and E) Mixture of peptides from SM and CNS cysts. The normalized optical density was calculated by dividing each individual O.D. by the cut-off value (mean value of non cysticercotic pigs plus two standard deviations). P-values are shown at the top of each figure. F) Heat map showing the individual response to antigenic peptide mixtures. The normalized optical density was transformed using Log<sub>2</sub>. White represents values near to the cut-off point, red represents values over the cut-off point (positive samples) and blue represents values below the cut-off point (negative samples).</p

    Immuno-localization and functional evaluation of host immunoglobulins purified from protein extracts of <i>Taenia solium</i> cysts.

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    <p>A) Immuno-localization of host IgG in cysts obtained from the central nervous system and skeletal muscle of pigs. B) Immunoglobulins present in total protein extracts of cysts were purified using a Sepharose 4B column coupled with Protein G. C). The purity of the bound IgG was evaluated by SDS-PAGE and western blotting using an anti-pig IgG coupled to HRP. D) The antibody activity of purified IgG was evaluated by ELISA. Samples of <i>T</i>. <i>solium</i> vesicular fluid and insoluble fraction were used to coat 96 well microtiter plates. Afterwards, the purified IgG was incubated overnight at 4°C under slow agitation. Then, the antigen-antibody reaction was developed using a colorimetric method. E) Recognition of cysts proteins by the purified IgG through western blotting. Samples of <i>T</i>. <i>solium</i> vesicular fluid and insoluble fraction were resolved through SDS-PAGE and then transferred onto a nitrocellulose membrane. The purified IgG from cysts protein extracts was used as primary antibody (for comparison sera from cysticercotic pigs was also included) and an anti-pig IgG coupled to HRP was used as secondary antibody. Lower right panel shows the reaction with the secondary antibody alone as control.</p

    Proteomic analysis of <i>Taenia solium</i> cysts.

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    <p>A) Table summarizing peptide and protein quantification from the nine samples. Proteins were collapsed to a final protein-level FDR < 2%. B) Fold change distributions of proteins of skeletal muscle (SM) cysts. C) Volcano plots showing P-value and the Log<sub>2</sub> (fold change CNS cysts/SM cysts) of proteins of SM and CNS cysts. D) Heat map showing the signature for <i>T</i>. <i>solium</i> proteins of SM and CNS cysts. E) Heat map showing the signature for the host (<i>Sus scrofa</i>) proteins quantified in protein extracts of SM and CNS cysts.</p

    Antigenic response space.

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    <p>The raw optical densities were analyzed using machine-learning methodologies. We determined the performance of (A) individual peptides measurements, (B) peptide mixtures measurements and (C) the combination of both strategies. Best/worst refers to the percentage of error (taking into account our n = 30; an error of 10 implies that three pig sera were not discriminated). Visual representation of the antigenic response space for multiple antigen testing (D) and <i>T</i>. <i>solium</i> cysts protein extracts (E).</p
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