17 research outputs found

    Transcriptional regulatory logic of the diurnal cycle in the mouse liver.

    Get PDF
    Many organisms exhibit temporal rhythms in gene expression that propel diurnal cycles in physiology. In the liver of mammals, these rhythms are controlled by transcription-translation feedback loops of the core circadian clock and by feeding-fasting cycles. To better understand the regulatory interplay between the circadian clock and feeding rhythms, we mapped DNase I hypersensitive sites (DHSs) in the mouse liver during a diurnal cycle. The intensity of DNase I cleavages cycled at a substantial fraction of all DHSs, suggesting that DHSs harbor regulatory elements that control rhythmic transcription. Using chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq), we found that hypersensitivity cycled in phase with RNA polymerase II (Pol II) loading and H3K27ac histone marks. We then combined the DHSs with temporal Pol II profiles in wild-type (WT) and Bmal1-/- livers to computationally identify transcription factors through which the core clock and feeding-fasting cycles control diurnal rhythms in transcription. While a similar number of mRNAs accumulated rhythmically in Bmal1-/- compared to WT livers, the amplitudes in Bmal1-/- were generally lower. The residual rhythms in Bmal1-/- reflected transcriptional regulators mediating feeding-fasting responses as well as responses to rhythmic systemic signals. Finally, the analysis of DNase I cuts at nucleotide resolution showed dynamically changing footprints consistent with dynamic binding of CLOCK:BMAL1 complexes. Structural modeling suggested that these footprints are driven by a transient heterotetramer binding configuration at peak activity. Together, our temporal DNase I mappings allowed us to decipher the global regulation of diurnal transcription rhythms in the mouse liver

    Quantifying ChIP-seq data:A spiking method providing an internal reference for sample-to-sample normalization

    Get PDF
    Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) experiments are widely used to determine, within entire genomes, the occupancy sites of any protein of interest, including, for example, transcription factors, RNA polymerases, or histones with or without various modifications. In addition to allowing the determination of occupancy sites within one cell type and under one condition, this method allows, in principle, the establishment and comparison of occupancy maps in various cell types, tissues, and conditions. Such comparisons require, however, that samples be normalized. Widely used normalization methods that include a quantile normalization step perform well when factor occupancy varies at a subset of sites, but may miss uniform genome-wide increases or decreases in site occupancy. We describe a spike adjustment procedure (SAP) that, unlike commonly used normalization methods intervening at the analysis stage, entails an experimental step prior to immunoprecipitation. A constant, low amount from a single batch of chromatin of a foreign genome is added to the experimental chromatin. This "spike" chromatin then serves as an internal control to which the experimental signals can be adjusted. We show that the method improves similarity between replicates and reveals biological differences including global and largely uniform changes

    Dynamic modeling of the TOR signaling pathway in yeast

    No full text
    This Master thesis presents a complete cycle in the use of models for the study of a complex pathway like the TOR pathway. Previous models were reproduced for the phosphatase part of the pathway, and the assumptions used and the results they provided were studied critically, along with the information content of the experimental data they are based on, thanks to a sensitivity analysis framework. This showed that most parameters can be estimated within high bounds of inaccuracy and that further experiments would be useful, some of which can be directly suggested by the analysis. Literature research gave way to extensions and modications of extisting models in dierent directions of the TOR pathway : Npr1, Sch9, Gln3 and Sfp1 regulations. For Gln3 regulation, new quantitative dynamic data was obtained for its localization upon Rapamycin treatment, and used for parameter estimation. The advantage of this new dataset was assessed. Further study of the models revealed that hypotheses could not be discriminated solely by fitting experimental data, but mutant results also gave important information, which nevertheless need to be taken carefully. A new model for Sfp1 control showed qualitatively correct behavior. Sensitivity analysis on this new model was done as well, which also showed that parameters for the non-phosphatase part of the pathway cannot be accurately estimated with the data available, although the dataset on new interactions appears to provide more information. In conclusion, this work shows the progression through creation of extensions to the TOR pathway, assessment of experimental needs, the obtention of experimental data for parameter estimation, and an assessment of the results of simulations and optimizatio

    Lipopeptides produced by Bacillus subtilis as new biocontrol products against fusariosis in ornamental plants

    No full text
    National audienceIn this study, we have investigated the effects of three lipopeptides (fengycin, surfactin and mycosubtilin) produced by different strains of Bacillus subtilis against the phytopathogenic fungi Fusarium oxysporum f. sp. iridacearum, which affects the ornamental bulb plant populations of Iris sp. The antifungal effects were tested using minimum inhibitory concentration assay, determination of mycelium growth and spore germination inhibition rates. Also, in vivo tests on infected rhizomes and scanning electron microscopy were employed. Mycosubtilin alone and in combination with fengycin or/and surfactin showed potent inhibitory activity at concentrations as low as 5gml(-1) which is 100 times lower compared to Topsin M, a common chemical fungicide frequently used against fusariosis in ornamental plants. An enhancement of mycosubtilin antifungal activity was observed when it was used in combination with surfactin due to a synergistic effect. At a concentration of 20gml(-1), mycosubtilin inhibited the growth of the mycelium up to 49% and the spore germination ability up to 26% in comparison to control. In addition, significant changes on the macro- and micro-morphology have been observed. The antifungal activity is related to the inhibition of spore germination and the irreversible damage of the hyphae cell wall. To the best of our knowledge, this is the first attempt to propose the lipopeptides as biopesticides against the fusariosis of ornamental plants

    Chromatin accessibility in <i>Bmal1</i><sup>-/-</sup> mice at ZT6 is generally similar as in the Wild-Type (WT) mice but is lower at BMAL1 sites.

    No full text
    <p>A. The <i>Rev-erbα</i> (left) and <i>Gsk3a</i> (right) promoters. DNase I signal (in red) is strongly reduced in <i>Bmal1</i><sup>-/-</sup> mice at sites bound by CLOCK:BMAL1 in WT mice (BMAL1 chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq) signal in blue) in the <i>Rev-erbα</i> promoter but is similar in WT and <i>Bmal1</i><sup>-/-</sup> mice at the <i>Gsk3a</i> promoter that are not bound by BMAL1. The vertical scale is the same for all three DNase I tracks, as well as for both BMAL1 ChiP-seq tracks. Wild-type ZT18 signals are lower (about half) than at ZT6 in both genes but not as low as in the <i>Bmal1</i><sup>-/-</sup> mice. B. Comparison of DNase I signals at ZT6 in <i>Bmal1</i><sup>-<b>/-</b></sup> versus WT mice. All DNase I hypersensitive sites (DHSs) overlapping BMAL1 ChIP-seq peaks in [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001069#pbio.2001069.ref017" target="_blank">17</a>] are shown (<i>n</i> = 1,555). The dashed lines indicate 4-fold difference. C. Boxplots showing DNase I intensity at the same sites as in B, at peak (ZT6) and trough (ZT18) activities of BMAL1 in the WT, and at ZT6 in <i>Bmal1</i><sup>-/-</sup> mice for all BMAL1-binding sites (green), BMAL1 sites with an associated expression phase between ZT2 and ZT10 (orange), and with a tandem E-box (grey). All pairwise comparisons (within the same color) between either ZT6 versus ZT18 or ZT6 versus ZT6 <i>Bmal1</i><sup>-/-</sup> are significant (<i>p</i> < 0.001). D–E. Same as B–C but using overlap with USF1 ChIP-seq peaks [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001069#pbio.2001069.ref074" target="_blank">74</a>] to select DHSs (<i>n</i> = 1,705).</p

    BMAL1 footprints indicate temporally changing protein–DNA complexes, consistent with binding of a heterotetramer to DNA.

    No full text
    <p>A. Genomic profiles of DNase I cuts around double E-boxes with a spacer of 6 bp (E1-E2 sp6). We selected <i>n</i> = 249 E1-E2 sp6 motifs overlapping a BMAL1 chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq) peak and show the average of profiles for loci classified as bound by the mixture model (posterior probability >0.5). At ZT6, we observed that nucleotides around both E-boxes are protected. In contrast, at ZT18, the width of the protected region is reduced by approximately half, with the second E-box no longer protected from digestion. The signals are anchored to the motif position. Orientation of sites and signals is according to the best match to the E1-E2 sp6 motif. In <i>Bmal1</i><sup><i>-/-</i></sup>, only one E-box appears occupied. B. Width (left-side <i>y</i>-axis, green) of the protected region in WT and in <i>Bmal1</i><sup><i>-/-</i></sup> mice for E1-E2 sp6 motifs occupied by BMAL1. Fraction of predicted occupied sites is shown in blue (right-side <i>y</i>-axis). C. Two views of the 3-D computational model of the CLOCK:BMAL1 heterotetramer showing two heterodimers of CLOCK:BMAL1 occupying an E1-E2 sp6 site. The two heterodimers are shown in green and blue, while darker green and darker blue correspond to BMAL1 and lighter colors to CLOCK proteins. Information content along the DNA strands is shown in grey with highly constrained nucleotides of the motif in red. D. Zoom on the interacting residuals on the PAS-B domain of CLOCK implicated in the heterotetramer formation.</p

    Distal DNase I Hypersensitive Sites (DHSs) help identify diurnally active transcription regulators.

    No full text
    <p>A. Scheme of the linear model to infer active transcription regulators: transcription factor (TF) motifs in DHSs within a symmetric window around active transcription start sites (TSSs) are used to explain diurnal rhythms in transcription. B. Fraction of explained temporal variance (deviance ratio) in RNA polymerase II (Pol II) loading (at the TSS of all actives genes) for WT and <i>Bmal1</i><sup>-/-</sup> mice, in function of the window size (radius) for DHS inclusion, shows a maximum at around 50 kb. Here, <i>α</i> = 0 was used in the glmnet (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001069#sec015" target="_blank">Materials and methods</a>). C–D. Inferred TF motif activities for WT and in <i>Bmal1</i><sup>-/-</sup> mice shown with amplitudes (distance from center) and peak times (clockwise, ZT0 at the top) using a window size of 50 kb. All 819 (WT) and 629 (<i>Bmal1</i><sup>-/-</sup>) motifs (overlap is 427) with nonzero activities are shown. Note though that most activities are very small and cluster in the center. Certain families of TFs are indicated in colors (full results are provided in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001069#pbio.2001069.s018" target="_blank">S4 Table</a>). Radial scale for activities is arbitrary but comparable in C and D. E. Quantification of western blots for pCREB (Ser 133 phosphorylation) and CREB in WT and <i>Bmal1</i><sup><i>-</i>/-</sup> genotypes (log<sub>2</sub> (pCREB/CREB)). Nuclear extracts from four independent livers were harvested every 2 h. Both genotypes showed a significant oscillation (<i>p</i> < 0.05, harmonic regression) of the mean signal from the four mice. Though the peak time in <i>Bmal1</i><sup>-/-</sup> mice is delayed by 1.8 h, the comparison of the rhythm in the two genotypes was not significant (<i>p</i> = 0.49, Chow test). Individual blots are shown in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001069#pbio.2001069.s007" target="_blank">S7 Fig</a>.</p
    corecore