EBP1 Is a Novel E2F Target Gene Regulated by Transforming Growth Factor-β

Regulation of gene expression requires transcription factor binding to specific DNA elements, and a large body of work has focused on the identification of such sequences. However, it is becoming increasingly clear that eukaryotic transcription factors can exhibit widespread, nonfunctional binding to genomic DNA sites. Conversely, some of these proteins, such as E2F, can also modulate gene expression by binding to non-consensus elements. E2F comprises a family of transcription factors that play key roles in a wide variety of cellular functions, including survival, differentiation, activation during tissue regeneration, metabolism, and proliferation. E2F factors bind to the Erb3-binding protein 1 (EBP1) promoter in live cells. We now show that E2F binding to the EBP1 promoter occurs through two tandem DNA elements that do not conform to typical consensus E2F motifs. Exogenously expressed E2F1 activates EBP1 reporters lacking one, but not both sites, suggesting a degree of redundancy under certain conditions. E2F1 increases the levels of endogenous EBP1 mRNA in breast carcinoma and other transformed cell lines. In contrast, in non-transformed primary epidermal keratinocytes, E2F, together with the retinoblastoma family of proteins, appears to be involved in decreasing EBP1 mRNA abundance in response to growth inhibition by transforming growth factor-β1. Thus, E2F is likely a central coordinator of multiple responses that culminate in regulation of EBP1 gene expression, and which may vary depending on cell type and context

A fast weak motif-finding algorithm based on community detection in graphs

BACKGROUND: Identification of transcription factor binding sites (also called ‘motif discovery’) in DNA sequences is a basic step in understanding genetic regulation. Although many successful programs have been developed, the problem is far from being solved on account of diversity in gene expression/regulation and the low specificity of binding sites. State-of-the-art algorithms have their own constraints (e.g., high time or space complexity for finding long motifs, low precision in identification of weak motifs, or the OOPS constraint: one occurrence of the motif instance per sequence) which limit their scope of application. RESULTS: In this paper, we present a novel and fast algorithm we call TFBSGroup. It is based on community detection from a graph and is used to discover long and weak (l,d) motifs under the ZOMOPS constraint (zero, one or multiple occurrence(s) of the motif instance(s) per sequence), where l is the length of a motif and d is the maximum number of mutations between a motif instance and the motif itself. Firstly, TFBSGroup transforms the (l, d) motif search in sequences to focus on the discovery of dense subgraphs within a graph. It identifies these subgraphs using a fast community detection method for obtaining coarse-grained candidate motifs. Next, it greedily refines these candidate motifs towards the true motif within their own communities. Empirical studies on synthetic (l, d) samples have shown that TFBSGroup is very efficient (e.g., it can find true (18, 6), (24, 8) motifs within 30 seconds). More importantly, the algorithm has succeeded in rapidly identifying motifs in a large data set of prokaryotic promoters generated from the Escherichia coli database RegulonDB. The algorithm has also accurately identified motifs in ChIP-seq data sets for 12 mouse transcription factors involved in ES cell pluripotency and self-renewal. CONCLUSIONS: Our novel heuristic algorithm, TFBSGroup, is able to quickly identify nearly exact matches for long and weak (l, d) motifs in DNA sequences under the ZOMOPS constraint. It is also capable of finding motifs in real applications. The source code for TFBSGroup can be obtained from http://bioinformatics.bioengr.uic.edu/TFBSGroup/

HDAC4 represses p21(WAF1/Cip1) expression in human cancer cells through a Sp1-dependent, p53-independent mechanism.

Cancer cells have complex, unique characteristics that distinguish them from normal cells, such as increased growth rates and evasion of anti-proliferative signals. Global inhibition of class I and II histone deacetylases (HDACs) stops cancer cell proliferation in vitro and has proven effective against cancer in clinical trials, at least in part, through transcriptional reactivation of the p21(WAF1/Cip1)gene. The HDACs that regulate p21(WAF1/Cip1) are not fully identified. Using small interfering RNAs, we found that HDAC4 participates in the repression of p21(WAF1/Cip1) through Sp1/Sp3-, but not p53-binding sites. HDAC4 interacts with Sp1, binds and reduces histone H3 acetylation at the Sp1/Sp3 binding site-rich p21(WAF1/Cip1) proximal promoter, suggesting a key role for Sp1 in HDAC4-mediated repression of p21(WAF1/Cip1). Induction of p21(WAF1/Cip1) mediated by silencing of HDAC4 arrested cancer cell growth in vitro and inhibited tumor growth in an in vivo human glioblastoma model. Thus, HDAC4 could be a useful target for new anti-cancer therapies based on selective inhibition of specific HDACs

The Condition-Dependent Transcriptional Landscape of Burkholderia pseudomallei

Burkholderia pseudomallei (Bp), the causative agent of the often-deadly infectious disease melioidosis, contains one of the largest prokaryotic genomes sequenced to date, at 7.2 Mb with two large circular chromosomes (1 and 2). To comprehensively delineate the Bp transcriptome, we integrated whole-genome tiling array expression data of Bp exposed to >80 diverse physical, chemical, and biological conditions. Our results provide direct experimental support for the strand-specific expression of 5,467 Sanger protein-coding genes, 1,041 operons, and 766 non-coding RNAs. A large proportion of these transcripts displayed condition-dependent expression, consistent with them playing functional roles. The two Bp chromosomes exhibited dramatically different transcriptional landscapes — Chr 1 genes were highly and constitutively expressed, while Chr 2 genes exhibited mosaic expression where distinct subsets were expressed in a strongly condition-dependent manner. We identified dozens of cis-regulatory motifs associated with specific condition-dependent expression programs, and used the condition compendium to elucidate key biological processes associated with two complex pathogen phenotypes — quorum sensing and in vivo infection. Our results demonstrate the utility of a Bp condition-compendium as a community resource for biological discovery. Moreover, the observation that significant portions of the Bp virulence machinery can be activated by specific in vitro cues provides insights into Bp's capacity as an “accidental pathogen”, where genetic pathways used by the bacterium to survive in environmental niches may have also facilitated its ability to colonize human hosts