Project description:In this study, we generate genomic maps of Mediator, Pol II, TBP, TFIIH, TFIIA, TFIIB, TFIIE, TFIIF, by ChIP coupled to next generation sequencing technology (ChIP-seq), in wild type strains from Saccharomyces cerevisiae and in a mutant for the Mediator essential subunit Med10
Project description:Purpose: To identify the differential TFIIB bindingl patterns during postnatal cardiac growth, pressure-induced cardiac hypertrophy and adult mouse hearts Methods: Hearts were extracted from 1-2day old C57 mice, from mice subjecetd to Transaortic coarctation or adult mice. The hearts were sent to Active Motif for TFIIB- ChIP-Seq. Results: In accordance with previosly published data (Sayed D, et. al. JBC, 2013 Jan 25;288(4):2546-58) with genome wide polII and H3K9ac status during cardiac hypertrophy (GSE50637), Denovo TFIIB recruitment was restricted to speclaized genes with cardiac hypertrophy.
Project description:Purpose: To identify the differential TFIIB bindingl patterns during postnatal cardiac growth, pressure-induced cardiac hypertrophy and adult mouse hearts Methods: Hearts were extracted from 1-2day old C57 mice, from mice subjecetd to Transaortic coarctation or adult mice. The hearts were sent to Active Motif for TFIIB- ChIP-Seq. Results: In accordance with previosly published data (Sayed D, et. al. JBC, 2013 Jan 25;288(4):2546-58) with genome wide polII and H3K9ac status during cardiac hypertrophy (GSE50637), Denovo TFIIB recruitment was restricted to speclaized genes with cardiac hypertrophy. Hearts were extracted from 1-2day old C57 mice, from mice subjecetd to Transaortic coarctation or adult mice. The hearts were sent to Active Motif for TFIIB- ChIP-Seq.
Project description:We introduce the functional generalized additive model (FGAM), a novel regression model for association studies between a scalar response and a functional predictor. We model the link-transformed mean response as the integral with respect to t of F{X(t), t} where F(·,·) is an unknown regression function and X(t) is a functional covariate. Rather than having an additive model in a finite number of principal components as in Müller and Yao (2008), our model incorporates the functional predictor directly and thus our model can be viewed as the natural functional extension of generalized additive models. We estimate F(·,·) using tensor-product B-splines with roughness penalties. A pointwise quantile transformation of the functional predictor is also considered to ensure each tensor-product B-spline has observed data on its support. The methods are evaluated using simulated data and their predictive performance is compared with other competing scalar-on-function regression alternatives. We illustrate the usefulness of our approach through an application to brain tractography, where X(t) is a signal from diffusion tensor imaging at position, t, along a tract in the brain. In one example, the response is disease-status (case or control) and in a second example, it is the score on a cognitive test. R code for performing the simulations and fitting the FGAM can be found in supplemental materials available online.
Project description:Experimental and bioinformatic studies of transcription initiation by RNA polymerase II (RNAP2) have revealed a mechanism of RNAP2 transcription initiation less uniform across gene promoters than initially thought. However, the general transcription factor TFIIB is presumed to be universally required for RNAP2 transcription initiation. Based on bioinformatic analysis of data, TFIIB knockdown in primary and transformed cell lines, and in vitro transcription experiments, we report that TFIIB is dispensable for transcription of most human promoters, but is essential for HSV-1 gene transcription and replication. We report a novel cell cycle TFIIB regulation and involvement of the acetylated TFIIB variant in chromosomal condensation. Taken together, these results establish a new paradigm for TFIIB functionality as a determinant of the human transcriptome, which when downregulated has potent anti-viral effects.
Project description:Although TFIIB is widely regarded as an initiation factor, recent reports have implicated it in multiple aspects of eukaryotic transcription. To investigate the broader role of TFIIB in transcription, we performed quantitative proteomic analysis of yeast TFIIB. We purified two different populations of TFIIB; one form soluble cell lysate, which is not engaged in transcription, and the other from chromatin fraction which yields the transcriptionally active form of the protein. TFIIB purified from the chromatin exhibits several interactions that explain its non-canonical roles in transcription. RNAPII, TFIIF and TFIIH were the only components of preinitiation complex with a significant presence in chromatin TFIIB. A notable feature was the substantial enrichment of all 3’ end processing-termination factors; CF1, CPF and Rat1 in chromatin-TFIIB preparation. These results corroborate the role of TFIIB in termination of transcription. Presence of the Lsm complex as well as TREX complex subunit Sub2 in chromatin-TFIIB opens the possibility of novel roles of TFIIB in synthesis-decay coupling and nucleocytoplasmic transport of mRNA. This multiplicity of functions may contribute to the preferential targeting of TFIIB during viral pathogenesis
Project description:A comparative ChIP-chip analysis of TFIIB and NC2 in human B cells reveals that basal core promoter architectures control the equilibrium between NC2 and preinitiation complexes. We conducted a comparative ChIP-chip and gene expression analysis of TFIIB in human B cells and analyze associated core promoter architectures. TFIIB occupancy relates well to gene expression, with the vast majority of promoters being GC-rich and lacking defined core promoter elements. TATA consensus and TATA-like motifs but not the previously in vitro defined TFIIB recognition elements (BREs) are enriched in approximately 5% of the genes. Further insight was obtained by performing a parallel ChIP-chip analysis of the TFIIB antagonist NC2. The latter identifies a highly related target gene set. Nonetheless, subpopulations show strong variations in TFIIB/NC2 ratios, with high NC2/TFIIB ratios correlating to promoters that show dispersed transcription start site patterns and lacking defined core elements. Conversely, high TFIIB/NC2 ratios select for conserved core promoter elements that include TATA and INR (initiator), the upstream TFIIB recognition element (BREu) and the downstream promoter element (DPE).
Project description:Background: Antibodies that target immune checkpoints such as cytotoxic T lymphocyte antigen 4 (CTLA 4) and the programmed cell death protein 1/ligand 1 (PD-1/PD-L1) are now a treatment option for multiple cancer types. However, as a monotherapy, objective responses only occur in a minority of patients. Chemotherapy is widely used in combination with immune checkpoint blockade (ICB). Although a variety of isolated immunostimulatory effects have been reported for several classes of chemotherapeutics, it is unclear which chemotherapeutics provide the most benefit when combined with ICB. Methods: We investigated 10 chemotherapies from the main canonical classes dosed at the clinically relevant maximum tolerated dose in combination with anti CTLA-4/anti-PD-L1 ICB. We screened these chemo-immunotherapy combinations in two murine mesothelioma models from two different genetic backgrounds, and identified chemotherapies that produced additive, neutral or antagonistic effects when combined with ICB. Using flow cytometry and bulk RNAseq, we characterized the tumor immune milieu in additive chemo-immunotherapy combinations. Results: 5-fluorouracil (5-FU) or cisplatin were additive when combined with ICB while vinorelbine and etoposide provided no additional benefit when combined with ICB. The combination of 5-FU with ICB augmented an inflammatory tumor microenvironment with markedly increased CD8+ T cell activation and upregulation of IFN , TNF and IL-1β signaling. The effective anti tumor immune response of 5-FU chemo-immunotherapy was dependent on CD8+ T cells but was unaffected when TNF or IL 1β cytokine signaling pathways were blocked. Conclusions: Our study identified additive and non-additive chemotherapy/ICB combinations and suggests a possible role for increased inflammation in the tumor microenvironment as a basis for effective combination therapy.