85 research outputs found

    DataSheet_1_After virus exposure, early bystander naïve CD8 T cell activation relies on NAD+ salvage metabolism.pdf

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    CD8 T cells play a central role in antiviral immunity. Type I interferons are among the earliest responders after virus exposure and can cause extensive reprogramming and antigen-independent bystander activation of CD8 T cells. Although bystander activation of pre-existing memory CD8 T cells is known to play an important role in host defense and immunopathology, its impact on naïve CD8 T cells remains underappreciated. Here we report that exposure to reovirus, both in vitro or in vivo, promotes bystander activation of naïve CD8 T cells within 24 hours and that this distinct subtype of CD8 T cell displays an innate, antiviral, type I interferon sensitized signature. The induction of bystander naïve CD8 T cells is STAT1 dependent and regulated through nicotinamide phosphoribosyl transferase (NAMPT)-mediated enzymatic actions within NAD+ salvage metabolic biosynthesis. These findings identify a novel aspect of CD8 T cell activation following virus infection with implications for human health and physiology.</p

    DataSheet_2_After virus exposure, early bystander naïve CD8 T cell activation relies on NAD+ salvage metabolism.docx

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    CD8 T cells play a central role in antiviral immunity. Type I interferons are among the earliest responders after virus exposure and can cause extensive reprogramming and antigen-independent bystander activation of CD8 T cells. Although bystander activation of pre-existing memory CD8 T cells is known to play an important role in host defense and immunopathology, its impact on naïve CD8 T cells remains underappreciated. Here we report that exposure to reovirus, both in vitro or in vivo, promotes bystander activation of naïve CD8 T cells within 24 hours and that this distinct subtype of CD8 T cell displays an innate, antiviral, type I interferon sensitized signature. The induction of bystander naïve CD8 T cells is STAT1 dependent and regulated through nicotinamide phosphoribosyl transferase (NAMPT)-mediated enzymatic actions within NAD+ salvage metabolic biosynthesis. These findings identify a novel aspect of CD8 T cell activation following virus infection with implications for human health and physiology.</p

    High-Level Secretion of Pregnancy Zone Protein Is a Novel Biomarker of DNA Damage-Induced Senescence and Promotes Spontaneous Senescence

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    Identification of unique and specific biomarkers to better detect and quantify senescent cells remains challenging. By a global proteomic profiling of senescent human skin BJ fibroblasts induced by ionizing radiation (IR), the cellular level of pregnancy zone protein (PZP), a presumable pan-protease inhibitor never been linked to cellular senescence before, was found to be decreased by more than 10-fold, while the level of PZP in the conditioned medium was increased concomitantly. This observation was confirmed in a variety of senescent cells induced by IR or DNA-damaging drugs, indicating that high-level secretion of PZP is a novel senescence-associated secretory phenotype. RT-PCR examination verified that the transcription of the PZP gene is enhanced in various cells at senescence or upregulated following DNA damage treatment in a p53-independent manner. Moreover, pretreatment with late pregnancy serum containing a high level of PZP led to inhibition of doxorubicin-induced senescence in A549 cells, and depletion of PZP in the pregnancy serum could enhance such inhibition. Finally, the addition of immuno-precipitated PZP complexes into tissue culture attenuated the growth of A549 cells and promoted the spontaneous senescence. Therefore, we revealed that high-level secretion of PZP is a novel and unique feature associated with DNA damage-induced senescence, and secreted PZP is a positive regulator of cellular senescence, particularly during the late stage of gestation

    Adapting an Isobaric Tag-Labeled Yeast Peptide Standard to Develop Targeted Proteomics Assays

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    Targeted proteomics strategies present a streamlined hypothesis-driven approach to analyze specific sets of pathways or disease related proteins. goDig is a quantitative, targeted tandem mass tag (TMT)-based assay that can measure the relative abundance differences for hundreds of proteins directly from unfractionated mixtures. Specific protein groups or entire pathways of up to 200 proteins can be selected for quantitative profiling, while leveraging sample multiplexing permits the simultaneous analysis of up to 18 samples. Despite these benefits, implementing goDig is not without challenges, as it requires access to an instrument application programming interface (iAPI), an elution order and spectral library, a web-based method builder, and dedicated companion software. In addition, the absence of an example test assay may dissuade researchers from testing or implementing goDig. Here, we repurpose the TKO11 standardwhich is commercially available but may also be assembled in-laband establish it as a de facto test assay for goDig. We build a proteome-wide goDig yeast library, quantify protein expression across several gene ontology (GO) categories, and compare these results to a fully fractionated yeast gold-standard data set. Essentially, we provide a guide detailing the goDig-based quantification of TKO11, which can also be used as a template for user-defined assays in other species

    Adapting an Isobaric Tag-Labeled Yeast Peptide Standard to Develop Targeted Proteomics Assays

    No full text
    Targeted proteomics strategies present a streamlined hypothesis-driven approach to analyze specific sets of pathways or disease related proteins. goDig is a quantitative, targeted tandem mass tag (TMT)-based assay that can measure the relative abundance differences for hundreds of proteins directly from unfractionated mixtures. Specific protein groups or entire pathways of up to 200 proteins can be selected for quantitative profiling, while leveraging sample multiplexing permits the simultaneous analysis of up to 18 samples. Despite these benefits, implementing goDig is not without challenges, as it requires access to an instrument application programming interface (iAPI), an elution order and spectral library, a web-based method builder, and dedicated companion software. In addition, the absence of an example test assay may dissuade researchers from testing or implementing goDig. Here, we repurpose the TKO11 standardwhich is commercially available but may also be assembled in-laband establish it as a de facto test assay for goDig. We build a proteome-wide goDig yeast library, quantify protein expression across several gene ontology (GO) categories, and compare these results to a fully fractionated yeast gold-standard data set. Essentially, we provide a guide detailing the goDig-based quantification of TKO11, which can also be used as a template for user-defined assays in other species

    Adapting an Isobaric Tag-Labeled Yeast Peptide Standard to Develop Targeted Proteomics Assays

    No full text
    Targeted proteomics strategies present a streamlined hypothesis-driven approach to analyze specific sets of pathways or disease related proteins. goDig is a quantitative, targeted tandem mass tag (TMT)-based assay that can measure the relative abundance differences for hundreds of proteins directly from unfractionated mixtures. Specific protein groups or entire pathways of up to 200 proteins can be selected for quantitative profiling, while leveraging sample multiplexing permits the simultaneous analysis of up to 18 samples. Despite these benefits, implementing goDig is not without challenges, as it requires access to an instrument application programming interface (iAPI), an elution order and spectral library, a web-based method builder, and dedicated companion software. In addition, the absence of an example test assay may dissuade researchers from testing or implementing goDig. Here, we repurpose the TKO11 standardwhich is commercially available but may also be assembled in-laband establish it as a de facto test assay for goDig. We build a proteome-wide goDig yeast library, quantify protein expression across several gene ontology (GO) categories, and compare these results to a fully fractionated yeast gold-standard data set. Essentially, we provide a guide detailing the goDig-based quantification of TKO11, which can also be used as a template for user-defined assays in other species

    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

    MINIMIZING THE CONDITION NUMBER TO CONSTRUCT DESIGN POINTS FOR POLYNOMIAL REGRESSION MODELS ∗

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    Abstract. In this paper we study a new optimality criterion, the K-optimality criterion, for constructing optimal experimental designs for polynomial regression models. We focus on the pth order polynomial regression model with symmetric design space [−1, 1]. For this model, we show that there is always a symmetric K-optimal design with exactly p + 1 support points including the boundary points −1 and 1. It is well known that the condition number for a positive definite matrix as the ratio of the maximum eigenvalue to the minimum eigenvalue is usually nonsmooth. We show that for our model, the condition number of the information matrix is continuously differentiable. Theoretical K-optimal designs are derived for p = 1 and 2. Numerical results are presented for 3 ≤ p ≤ 10

    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

    Proteome-Wide Evaluation of Two Common Protein Quantification Methods

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    Proteomics experiments commonly aim to estimate and detect differential abundance across all expressed proteins. Within this experimental design, some of the most challenging measurements are small fold changes for lower abundance proteins. While bottom-up proteomics methods are approaching comprehensive coverage of even complex eukaryotic proteomes, failing to reliably quantify lower abundance proteins can limit the precision and reach of experiments to much less than the identifiedî—¸let alone totalî—¸proteome. Here we test the ability of two common methods, a tandem mass tagging (TMT) method and a label-free quantitation method (LFQ), to achieve comprehensive quantitative coverage by benchmarking their capacity to measure 3 different levels of change (3-, 2-, and 1.5-fold) across an entire data set. Both methods achieved comparably accurate estimates for all 3-fold-changes. However, the TMT method detected changes that reached statistical significance three times more often due to higher precision and fewer missing values. These findings highlight the importance of refining proteome quantitation methods to bring the number of usefully quantified proteins into closer agreement with the number of total quantified proteins
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