Identification of endogenous genes regulated by heterochromatin protein 1 (HP1) in vivo

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Unraveling microalgal molecular interactions using evolutionary and structural bioinformatics

Microalgae are unicellular microorganisms indispensible for environmental stability and life on earth, because they produce approximately half of the atmospheric oxygen, with simultaneously feeding on the harmful greenhouse gas carbon dioxide. Using gene fusion analysis, a series of five fusion/fission events was identified, that provided the basis for critical insights to their evolutionary history. Moreover, the three-dimensional structures of both the fused and the component proteins were predicted, allowing us to envisage putative protein-protein interactions that are invaluable for the efficient usage, handling and exploitation of microalgae. Collectively, our proposed approach on the five fusion/fission alga protein events contributes towards the expansion of the microalgae knowledgebase, bridging protein evolution of the ancient microalgal species and the rapidly evolving, modern, bioinformatics field. (C) 2013 Elsevier B.V. All rights reserved

Early Transcriptome Signatures from Immunized Mouse Dendritic Cells Predict Late Vaccine-Induced T-Cell Responses

International audienceSystems biology offers promising approaches for identifying response-specific signatures to vaccination and assessing their predictive value. Here, we designed a modelling strategy aiming to predict the quality of late T-cell responses after vaccination from early transcriptome analysis of dendritic cells. Using standardized staining with tetramer, we first quantified antigen-specific T-cell expansion 5 to 10 days after vaccination with one of a set of 41 different vaccine vectors all expressing the same antigen. Hierarchical clustering of the responses defined sets of high and low T cell response inducers. We then compared these responses with the transcriptome of splenic dendritic cells obtained 6 hours after vaccination with the same vectors and produced a random forest model capable of predicting the quality of the later antigen-specific T-cell expansion. The model also successfully predicted vector classification as low or strong T-cell response inducers of a novel set of vaccine vectors, based on the early transcriptome results obtained from spleen dendritic cells, whole spleen and even peripheral blood mononuclear cells. Finally, our model developed with mouse datasets also accurately predicted vaccine efficacy from literature-mined human datasets

Hepatitis C virus modulates lipid regulatory factor Angiopoietin-like 3 gene expression by repressing HNF-1 alpha activity

Background & Aims: HCV relies on host lipid metabolism to complete its life cycle and HCV core is crucial to this interaction. Liver secreted ANGPTL-3 is an LXR-and HNF-1 alpha-regulated protein, which plays a key role in lipid metabolism by increasing plasma lipids via inhibition of lipase enzymes. Here we aimed to investigate the modulation of ANGPTL-3 by HCV core and identify the molecular mechanisms involved. Methods: qRT-PCR and ELISA were used to assess ANGPTL-3 mRNA and protein levels in HCV patients, the JFH-1 infectious system and liver cell lines. Transfections, chromatin immunoprecipitation and immunofluorescence delineated parts of the molecular mechanisms implicated in the core-mediated regulation of ANGPTL-3 gene expression. Results: ANGPTL-3 gene expression was decreased in HCV-infected patients and the JFH-1 infectious system. mRNA and promoter activity levels were down-regulated by core. The response was lost when an HNF-1 alpha element in ANGPTL-3 promoter was mutated, while loss of HNF-1 alpha DNA binding to this site was recorded in the presence of HCV core. HNF-1 alpha mRNA and protein levels were not altered by core. However, trafficking between nucleus and cytoplasm was observed and then blocked by an inhibitor of the HNF-1 alpha-specific kinase Mirk/Dyrk1B. Transactivation of LXR/RXR signalling could not restore coremediated down-regulation of ANGPTL-3 promoter activity. Conclusions: ANGPTL-3 is negatively regulated by HCV in vivo and in vitro. HCV core represses ANGPTL-3 expression through loss of HNF-1 alpha binding activity and blockage of LXR/RXR transactivation. The putative ensuing increase in serum lipid clearance and uptake by the liver may sustain HCV virus replication and persistence. (C) 2013 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved

Modelling strategy.

<p>(i) For each pre-processed dataset, composed of microarray measures for mice injected with vector 1 (V1.1, V1.2 …) and control (C1.1, C1.2 …), one hundred datasets were created by bootstrapping samples among V and C. (ii) Ranked gene lists, according to the eBayes statistical comparison of vector and control conditions, were generated. (iii) Potential signatures were tested for enrichment on each of the 100 ranked gene lists by GSEA. The resulting NES matrix was then used to build the random forest model.</p

Strategy followed in this study for a high-performance predictive model of transcriptome datasets obtained from new vector platforms, cells from whole organs (spleen, blood).

<p>RF: random forest.</p

Vector class prediction efficiency.

<p>Vector class prediction efficiency.</p

LCMV gp33-41 model antigen-expressing/displaying vector T-cell response analysis.

<p>A. Evaluation of gp33-41 specific T-cell frequency in mice immunized with Qb_1 or Qb_5 VLPs, with rAd_1 and control naive mice, by H-2Db:gp33-41 tetramer staining. B. For each vector tested, gp33-41 antigen-specific responses were evaluated at days 5, 7 and 10 in groups of 3–5 vaccinated mice. The normalized “CD8 T-cell expansion” value was calculated as the average of the peak response for each mouse against the value obtained for the internal standard experimental group (rAd_1). C. Hierarchical clustering (Euclidean/Ward.D2) performed on normalized T-cell response values defined as “Weak” (cluster 1) and “Strong” (clusters 2 and 3) vectors. Vectors in red were used to build the initial prediction model (see Model stability and confidence in the <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004801#sec002" target="_blank">Results</a> section).</p

Gene network analysis in “Weak” and “Strong” vectors.

<p>A: Selection of STAT-1 related genes derived from Sig1 of the RFM model were targeted on Ingenuity Pathway Analysis (IPA). B: CH25H, a gene selected in one of the other 26 important signatures of the model, was targeted as the key gene on IPA. The grow functionality was used to display all known direct and indirect interactions with CH25H, except miRNA. The biological interactions of CH25H are displayed on A (black arrows). Colors depend on statistical analyses (red: upregulated, green: downregulated) performed on rAd_1, AP205_1, MPY_3bis and BCG_2 vector datasets; color intensities were set to be in the same range in all experiments.</p

Predictions of human PBMC transcriptome data derived 6, 24 and 72 hours after vaccination by MRKAd5/HIV published in [25].

<p>Predictions of human PBMC transcriptome data derived 6, 24 and 72 hours after vaccination by MRKAd5/HIV published in [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004801#pcbi.1004801.ref025" target="_blank">25</a>].</p