ANCAC: amino acid, nucleotide, and codon analysis of COGs – a tool for sequence bias analysis in microbial orthologs

<p>Abstract</p> <p>Background</p> <p>The COG database is the most popular collection of orthologous proteins from many different completely sequenced microbial genomes. Per definition, a cluster of orthologous groups (COG) within this database exclusively contains proteins that most likely achieve the same cellular function. Recently, the COG database was extended by assigning to every protein both the corresponding amino acid and its encoding nucleotide sequence resulting in the NUCOCOG database. This extended version of the COG database is a valuable resource connecting sequence features with the functionality of the respective proteins.</p> <p>Results</p> <p>Here we present ANCAC, a web tool and MySQL database for the analysis of amino acid, nucleotide, and codon frequencies in COGs on the basis of freely definable phylogenetic patterns. We demonstrate the usefulness of ANCAC by analyzing amino acid frequencies, codon usage, and GC-content in a species- or function-specific context. With respect to amino acids we, at least in part, confirm the cognate bias hypothesis by using ANCAC’s NUCOCOG dataset as the largest one available for that purpose thus far.</p> <p>Conclusions</p> <p>Using the NUCOCOG datasets, ANCAC connects taxonomic, amino acid, and nucleotide sequence information with the functional classification via COGs and provides a GUI for flexible mining for sequence-bias. Thereby, to our knowledge, it is the only tool for the analysis of sequence composition in the light of physiological roles and phylogenetic context without requirement of substantial programming-skills.</p

AnnoMiner is a new web-tool to integrate epigenetics, transcription factor occupancy and transcriptomics data to predict transcriptional regulators

International audienceGene expression regulation requires precise transcriptional programs, led by transcription factors in combination with epigenetic events. Recent advances in epigenomic and transcriptomic techniques provided insight into different gene regulation mechanisms. However, to date it remains challenging to understand how combinations of transcription factors together with epigenetic events control cell-type specific gene expression. We have developed the AnnoMiner web-server, an innovative and flexible tool to annotate and integrate epigenetic, and transcription factor occupancy data. First, AnnoMiner annotates user-provided peaks with gene features. Second, AnnoMiner can integrate genome binding data from two different transcriptional regulators together with gene features. Third, AnnoMiner offers to explore the transcriptional deregulation of genes nearby, or within a specified genomic region surrounding a user-provided peak. AnnoMiner’s fourth function performs transcription factor or histone modification enrichment analysis for user-provided gene lists by utilizing hundreds of public, high-quality datasets from ENCODE for the model organisms human, mouse, Drosophila and C. elegans . Thus, AnnoMiner can predict transcriptional regulators for a studied process without the strict need for chromatin data from the same process. We compared AnnoMiner to existing tools and experimentally validated several transcriptional regulators predicted by AnnoMiner to indeed contribute to muscle morphogenesis in Drosophila . AnnoMiner is freely available at http://chimborazo.ibdm.univ-mrs.fr/AnnoMiner/

Thogoto virus ML protein inhibits IFN-α/β production by interacting with TFIIB.

<p>A) Volcano plot of proteins enriched in ML vs. M pulldown in HEK293 cells and identified by AP-LC-MS/MS. HA-tagged M or ML proteins were overexpressed in 4 biological replicates. B) Schematic representation of ML protein and its mutants not binding TFIIB or CAPN15. C) IP of GST-tagged M or ML (wt and mut) and co-IP of FLAG-tagged CAPN15 and TFIIB transiently overexpressed in HEK293 cells. Western blot is a representative of two independent experiments with similar results. D) IFN-α/β levels after infection with THOV wt, ΔML or mutant ML(SW) 24 h.p.i. SN from infected HeLa cells were applied to 293T Mx1-luc. *—p value < 0.05, NS–non-significant. Bar graph shows mean with SD of three technical replicates and is a representative of four independent experiments with similar results. Significance was estimated with Kruskal-Wallis test with Dunn’s multiple comparison post-test.</p

Transcriptome analysis of THOV-induced changes suggests broad but selective effect of ML.

<p>A) RNA synthesis rate in THOV infected Vero cells. Newly synthesized RNA was labelled with [3H]-5-Uridine at 1, 10 and 14 hours post infection. Presented is total RNA fraction as mean and SD from three technical replicates. B) qPCR analysis of IFITs, THOV NP transcript and GAPDH expression in HeLa cells after infection with THOV-wt, THOV-ΔML and THOV-SW for 16 hours. Presented are means and SD from three independent infection experiments. C) 2D-scatter plot of transcriptome analysis of HeLa cells infected with THOV-wt, THOV-ΔML and THOV-SW for 16 hours in three biological replicates. X axis represents log2 fold changes between mock and THOV-wt (green dots), Y axis shows log2 fold changes between mock and THOV-ΔML (blue dots). Changes occurring in wt and ΔML infections are shown in orange. Unchanged genes are shown in grey. Numbers are presented in a pie chart. Differentially regulated genes were showing at least 2-fold change with a q value < 0.05. D) GO term over-representation analysis of differentially upregulated genes by THOV ΔML and THOV ML (SW/AA) compared to THOV wt performed with InnateDB analysis tool. S–signalling, R–regulation, TF–transcription factor.</p

ML or TFIIB-depletion-mediated regulation of innate immune response and general transcription.

<p>When the cells are stimulated with a ligand, expression of a responsive gene can be activated by de novo recruitment of Pol II, which requires assembly of PIC (mode 1), or by releasing paused Pol II into the gene body (mode 2). In the presence of ML or after TFIIB depletion, expression of genes regulated by mode 1 (mostly cytokines and antiviral effector molecules) is severely impaired, while genes regulated by mode 2 (signalling components and housekeeping genes) continue to be expressed normally.</p

TFIIB depletion preferentially affects a subset of inflammatory cytokines and antiviral effector genes.

<p>A) Viability of HeLa cells after TFIIB knockdown at indicated time points. HeLa cells were treated with indicated siRNAs for 24, 48 and 72 hours and knockdown was validated by Western blot analysis. Cell viability was assessed by MTT assay. The bar graph shows mean and SD of three technical replicates and is a representative of two independent experiments with similar results. B) 2D-scatter plot of transcriptome analysis of HeLa cells before and after TFIIB knockdown mock-treated or stimulated with TNF-α in three biological replicates. HeLa cells were electroporated with Scrambled or TFIIB-targeting siRNAs. In 24 hours they were left untreated or stimulated with TNF-α (20 ng/ml) for 2 hours. Total RNA was extracted and analysed by RNA-seq. X axis shows log2 fold changes between mock-treated and TNF-α-treated cells with non-targeting siRNA (green dots), Y axis represents log2 fold changes between TNF-α-treated Scrambled-transfected cells and TNF-treated siTFIIB-transfected cells (blue dots). Genes upregulated by TNF-α in non-targeted cells and downregulated by TFIIB knockdown are shown in red. Genes upregulated by TNF-α in non-targeted cells and not regulated by TFIIB knockdown are shown in black. Numbers are shown in the scheme. Differentially regulated genes were showing at least 2-fold change with a q value < 0.05. C) qPCR analysis of genes regulated by TNF-α stimulation and affected (red) or non-affected (black) by TFIIB knockdown in HeLa cells. Bar graphs show representative genes. Scatter plots show all genes analysed. Dashed lines are showing the direction of change for affected (red) and non-affected (black) genes. Log2 fold changes are shown relative to Scrambled-transfected mock-treated cells. D) qPCR analysis of genes regulated by IFN-α stimulation. E) qPCR analysis of genes regulated by EGF stimulation. For all stimuli HeLa cells were electroporated with indicated siRNAs and in 16 hours stimulated with indicated ligands for 4 hours with subsequent RNA extraction. qPCR analysis was performed in two technical replicates in two independent experiments.</p

ML sequesters TFIIB from the nucleus, but does not cause its degradation.

<p>A) Confocal immunofluorescence analysis of HeLa Kyoto cells stably expressing GFP-TFIIB infected with THOV wt, THOV-ΔML or THOV-SW mutants for 24 hours at MOI 3. HeLa cells were treated as indicated, fixed and stained with GFP-DyLight488, THOV NP+rbAlexa546 and DAPI and subjected to confocal microscopy. Images are representative of two independent experiments with similar results. White bar – 10 μm. B) Confocal immunofluorescence analysis of HeLa Kyoto cells stably expressing GFP-TFIIB and transiently transfected with HA-M or HA-ML for 16 hours. HeLa cells were treated as indicated, fixed and stained with GFP-DyLight488, HA+msAlexa594 and DAPI and subjected to confocal microscopy. Images are representative of four independent experiments with similar results. White bar – 10 μm. C) Cytoplasmic-nuclear fractionation of Vero cells transiently transfected with HA-tagged M or ML for 24 hours. Depicted is endogenous TFIIB. Western blot is a representative of three experiments with similar results. D) Cytoplasmic-nuclear fractionation of Vero cells transiently transfected with FLAG-TFIIB and HA-tagged M or ML for 24 hours. Western blot is a representative of three experiments with similar results. E) Total protein intensity of TFIIB as defined by iBAQ, levels of newly synthesized TFIIB as determined from heavy intensities, and translation rates of identified proteins determined from H (newly synthesized)/L (total) ratios presented as box-whisker plots with whiskers showing 10–90 percentile. Protein levels were estimated in four biological replicates.</p

Multiple but not all inducible promoters are repressed by ML.

<p>(A-C) Reporter assays in HEK293 cells, where Firefly luciferase under indicated promoters was transfected together with EF-1a Renilla and M/ML/ML-SW. 24 h.p.t. cells were treated with indicated stimuli for 16 hours and the luciferase activity was measured. Shown is fold induction (mean and SD) over untreated cells from three independent experiments performed in six technical replicates. *—p<0.05; **—p<0.01; ***—p<0.001; ns–not significant. D) qPCR analysis of HeLa FlipIn cells expressing stably integrated ML from Tet-On promoter. HeLa cells were left untreated or treated with Doxycycline for 24h and subsequently stimulated with EGF for 16 hours. Total RNA was extracted and expression of indicated genes measured by qPCR. Shown are expression levels in relation to the non-Doxycycline treated unstimulated condition. The bar graphs show mean +/- error from two technical replicates and are representative of two independent experiments with similar results.</p

Genes subject to TFIIB regulation require <i>de novo</i> Pol II recruitment.

<p>A) Schematic representation of profile plots of the genes affected (red) and non-affected (black) by TFIIB knockdown in RNA-seq (top panel) and qPCR screen (bottom panel). B) Gene-averaged occupancy profiles of TFIIB, Pol II, NELF-A and DSIF for genes affected (red) or non-affected (black) by TFIIB depletion and for the genome background (blue). Embedded boxplots show the distribution of ChIP-Seq read coverage in the downstream promoter (Pol II, NELF, DSIF) or promoter (TFIIB) regions across genes. C) Distribution of pausing indices (pi) between affected and non-affected genes (pi>2 can be considered paused).</p

The alternative cap-binding complex is required for antiviral defense in vivo

International audienc