DNA Binding Sites For Transcription Factors Research Articles

The CREB Site in the Proximal Enhancer Is Critical for Cooperative Interaction with the Other Transcription Factor Binding Sites To Enhance Transcription of the Major Intermediate-Early Genes in Human Cytomegalovirus-Infected Cells

One of the two SP1 sites in the proximal enhancer of the human cytomegalovirus (HCMV) major immediate-early (MIE) promoter is essential for transcription in human fibroblast cells (H. Isomura, M. F. Stinski, A. Kudoh, T. Daikoku, N. Shirata, and T. Tsurumi, J. Virol. 79:9597-9607, 2005). Upstream of the two SP1 sites to -223 relative to the +1 transcription start site, there are an additional five DNA binding sites for eukaryotic transcription factors. We determined the effects of the various transcription factor DNA binding sites on viral MIE RNA transcription, viral gene expression, viral DNA synthesis, or infectious virus production. We prepared recombinant HCMV bacterial artificial chromosome (BAC) DNAs with either one site missing or one site present upstream of the two SP1 sites. Infectious recombinant HCMV BAC DNAs were transfected into various cell types to avoid the effect of the virion-associated transactivators. Regardless of the cell type, which included human fibroblast, endothelial, and epithelial cells, the CREB site had the most significant and independent effect on the MIE promoter. The other sites had a minor independent effect. However, the combination of the different transcription factor DNA binding sites was significantly stronger than multiple duplications of the CREB site. These findings indicate that the CREB site in the presence of the other sites has a major role for the replication of HCMV.

Sequence length limits for controlling false positives in discovering nucleotide sequence motifs

In the study of motif discovery, especially the transcription factor DNA binding sites discovery, a too long input sequence would return non-informative motifs rather than those biological functional motifs. This paper gave theoretical analyses and computational experiments to suggest the length limits of the input sequence. When the sequence length exceeds a certain critical point, the probability of discovering the motif decreases sharply. The work not only gave an explanation on the unsatisfying results of the existed motif discovery problems that the input sequence length might be too long and exceed the point, but also provided an estimation of input sequence length we should accept to get more meaningful and reliable results in motif discovery.

An efficient method for statistical significance calculation of transcription factor binding sites

Various statistical models have been developed to describe the DNA binding preference of transcription factors, by which putative transcription factor binding sites (TFBS) can be identified according to scores assigned. Statistical significance of these scores, usually known as the p-value, play a critical role in identification. We developed an efficient algorithm to provide precise calculation of the statistical significance, remarkably enhancing the calculation efficiency by reducing the time complexity from an exponent scale to a linear scale, and successfully extended the application of this algorithm to a wide range of models, from the commonly used position weight matrix models to the complicated Bayesian Network models. Further, we calculated p-values of all transcription factor DNA binding sites recorded in the database, JASPAR, and based on these, we investigated some unseen properties of p-values as a whole, such as the p-value distribution of different models and the p-value variance according to changed scoring schemes. We hope that our algorithm and the result of computational experiments would offer an improved solution to the statistical significance of transcription factor binding sites. The software to implement our method can be downloaded from http://pcal.biosino.org/pCal.html.

An approach to predict transcription factor DNA binding site specificity based upon gene and transcription factor functional categorization

To understand transcription regulatory mechanisms, it is indispensable to investigate transcription factor (TF) DNA binding preferences. We noted that the generally acknowledged information of functional annotations of TFs as well as that of their target genes should provide useful hints in determining TF DNA binding preferences. In this contribution, we developed an integrative method based on the Nearest Neighbor Algorithm, to predict DNA binding preferences through integrating both the functional/structural information of TFs and the interaction between TFs and their targets. The accuracy of cross-validation tests on the dataset consisting of 3430 positive samples and 7000 negative samples reaches 87.0% for 10-fold cross-validation and 87.9% for jackknife cross-validation test, which is a much better result than that in our previous work. The prediction result indicates that the improved method we developed could be a powerful approach to infer the TF DNA preference in silico. Supplementary data are available at Bioinformatics online.

Hierarchy and feedback in the evolution of the Escherichia coli transcription network

The Escherichia coli transcription network has an essentially feedforward structure, with abundant feedback at the level of self-regulations. Here, we investigate how these properties emerged during evolution. An assessment of the role of gene duplication based on protein domain architecture shows that (i) transcriptional autoregulators have mostly arisen through duplication, whereas (ii) the expected feedback loops stemming from their initial cross-regulation are strongly selected against. This requires a divergent coevolution of the transcription factor DNA-binding sites and their respective DNA cis-regulatory regions. Moreover, we find that the network tends to grow by expansion of the existing hierarchical layers of computation, rather than by addition of new layers. We also argue that rewiring of regulatory links due to mutation/selection of novel transcription factor/DNA binding interactions appears not to significantly affect the network global hierarchy, and that horizontally transferred genes are mainly added at the bottom, as new target nodes. These findings highlight the important evolutionary roles of both duplication and selective deletion of cross-talks between autoregulators in the emergence of the hierarchical transcription network of E. coli.

Curcumin Suppresses AP1 Transcription Factor-dependent Differentiation and Activates Apoptosis in Human Epidermal Keratinocytes

The diet-derived cancer preventive agent, curcumin, inhibits skin cancer cell proliferation and tumor formation. However, its effect on normal human keratinocyte differentiation, proliferation, and apoptosis has not been adequately studied. Involucrin (hINV) is a marker of keratinocyte differentiation and a useful model for the study of chemopreventive agent action. We show that curcumin suppresses the differentiation agent-dependent activation of hINV gene expression and that an AP1 transcription factor DNA binding site in the hINV gene is required for this regulation. A protein kinase C, Ras, MEKK1, MEK3 signaling cascade controls hINV expression by regulating AP1 factor level. Curcumin treatment inhibits the novel protein kinase C-, Ras-, and MEKK1-dependent activation of hINV promoter activity and reduces the differentiation agent-dependent increase in AP1 factor level and DNA binding. This reduction requires proteasome function. In addition, curcumin treatment reduces cell number, which is associated with a reduced cyclin and cdk1 levels. Curcumin treatment also suppresses the Bcl-xL level, leading to reduced mitochondrial membrane potential and increased cleavage of procaspases and poly(ADP-ribose) polymerase. These studies provide important insights regarding the mechanism whereby curcumin acts as a chemopreventive agent in normal human epidermis.

The Relationship between Intranuclear Mobility of the NF-κB Subunit p65 and Its DNA Binding Affinity

It has been hypothesized that the main determinant of the intranuclear mobility of transcription factors is their ability to bind DNA. In the present study, we have extensively tested the relationship between the intranuclear mobility of the NF-kappaB subunit p65 and binding to its consensus target sequence. The affinity of p65 for this binding site is altered by mutation of specific acetylation sites, so these mutants provide a model system to study the relationship between specific DNA binding affinity and intranuclear mobility. DNA binding affinity was measured in vitro using an enzyme-linked immunosorbent assay-based method, and intranuclear mobility was measured using the fluorescence recovery after photobleaching technique on yellow fluorescent protein-tagged p65 constructs. A negative correlation was observed between DNA binding affinity and intranuclear mobility of p65 acetylation site mutants. However, moving the yellow fluorescent protein tag from the C terminus of p65 to the N terminus resulted in an increased mobility but did not significantly affect DNA binding affinity. Thus, all changes in DNA binding affinity produce alterations in mobility, but not vice versa. Finally, a positive correlation was observed between mobility and the randomness of the intranuclear distribution of p65. Our data are in line with a model in which the intranuclear mobility and distribution of a transcription factor are determined by its affinity for specific DNA sequences, which may be altered by protein-protein interactions.

EVOPRINTER, a multigenomic comparative tool for rapid identification of functionally important DNA

Here, we describe a multigenomic DNA sequence-analysis tool, evoprinter, that facilitates the rapid identification of evolutionary conserved sequences within the context of a single species. The evoprinter output identifies multispecies-conserved DNA sequences as they exist in a reference DNA. This identification is accomplished by superimposing multiple reference DNA vs. test-genome pairwise blat (blast-like alignment tool) readouts of the reference DNA to identify conserved nucleotides that are shared by all orthologous DNAs. evoprinter analysis of well characterized genes reveals that most, if not all, of the conserved sequences are essential for gene function. For example, analysis of orthologous genes that are shared by many vertebrates identifies conserved DNA in both protein-encoding sequences and noncoding cis-regulatory regions, including enhancers and mRNA microRNA binding sites. In Drosophila, the combined mutational histories of five or more species affords near-base pair resolution of conserved transcription factor DNA-binding sites, and essential amino acids are revealed by the nucleotide flexibility of their codon-wobble position(s). Conserved small peptide-encoding genes, which had been undetected by conventional gene-prediction algorithms, are identified by the codon-wobble signatures of invariant amino acids. Also, evoprinter allows one to assess the degree of evolutionary divergence between orthologous DNAs by highlighting differences between a selected species and the other test species.

Transcription regulation: a genomic network

The transcriptional regulatory system plays a central role in directing gene expression changes in response to internal and external stimuli. In this talk, I will present our group's computational studies on transcription regulation in yeast, ranging from large-scale experimental studies to computational analyses of regulatory networks. In the first half I will introduce results from ChIp-chip experiments that identify genome-wide DNA-binding sites of transcription factors, particularly focusing on the cell cycle regulatory system. In the second half I will discuss how these observations fit in with the idea of a genomic regulatory network, and examine the effects of such networks on gene expression levels. Finally, I will introduce the concept of dynamic network usage in the context of transcription regulation, and how specific regulatory pathways are employed to bring about these transitions.

Evolution of transcription factor DNA binding sites

In bioinformatics, binding of transcription regulatory factors to the cognate binding sites is usually described by sequence-specific binding energy, which is estimated from a training sample of sites. This model implies that all binding sites with binding energy above some threshold are functional and site sequence variations should be considered neutral until they do not reduce this energy below the threshold. To quantify this energy, the binding profile (positional weight matrix, PWM) model or consensus-based model is usually applied. Here we show that in many cases available data are not sufficient to construct a relevant PWM, and modified consensus-based model could be more effective to describe binding properties. Further, using the data about binding sites of several transcription factors, we demonstrate that some non-consensus nucleotides in “orthologous sites” (that is, binding sites of the same factor upstream of orthologous genes), which have been believed to be irrelevant or even hindering the regulation, are evolutionary very stable and specific for the regulated gene. For each two considered genomes, the number of substitutions between non-consensus nucleotides is far less than the expected number of neutral substitutions. Moreover, in several positions of binding sites regulating different genes, there are non-consensus nucleotides conserved in distant genomes. It means that there exists a selection pressure, which results in the stability of non-consensus nucleotides.

The p53MH algorithm and its application in detecting p53-responsive genes.

A computer algorithm, p53MH, was developed, which identifies putative p53 transcription factor DNA-binding sites on a genomewide scale with high power and versatility. With the sequences from the human and mouse genomes, putative p53 DNA-binding elements were identified in a scan of 2,583 human genes and 1,713 mouse orthologs based on the experimental data of el-Deiry et al. [el-Deiry, W. S., Kern, S. E., Pietenpol, J. A., Kinzler, K. W. & Vogelstein, B. (1992) Nat. Genet. 1, 45-49] and Funk et al. [Funk, W. D., Pak, D. T., Karas, R. H., Wright, W. E. & Shay, J. W. (1992) Mol. Cell. Biol. 12, 2866-2871] (http://linkage.rockefeller.edu/p53). The p53 DNA-binding motif consists of a 10-bp palindrome and most commonly a second related palindrome linked by a spacer region. By scanning from the 5' to 3' end of each gene with an additional 10-kb nucleotide sequence appended at each end (most regulatory DNA elements characterized in the literature are in these regions), p53MH computes the binding likelihood for each site under a discrete discriminant model and then outputs ordered scores, corresponding site positions, sequences, and related information. About 300 genes receiving scores greater than a theoretical cut-off value were identified as potential p53 targets. Semiquantitative reverse transcription-PCR experiments were performed in 2 cell lines on 16 genes that were previously unknown regarding their functional relationship to p53 and were found to have high scores in either proximal promoter or possible distal enhancer regions. Ten (approximately 63%) of these genes responded to the presence of p53.

Experimental analysis and computer prediction of CTF/NFI transcription factor DNA binding sites

Accurate prediction of transcription factor binding sites is needed to unravel the function and regulation of genes discovered in genome sequencing projects. To evaluate current computer prediction tools, we have begun a systematic study of the sequence-specific DNA-binding of a transcription factor belonging to the CTF/NFI family. Using a systematic collection of rationally designed oligonucleotides combined with an in vitro DNA binding assay, we found that the sequence specificity of this protein cannot be represented by a simple consensus sequence or weight matrix. For instance, CTF/NFI uses a flexible DNA binding mode that allows for variations of the binding site length. From the experimental data, we derived a novel prediction method using a generalised profile as a binding site predictor. Experimental evaluation of the generalised profile indicated that it accurately predicts the binding affinity of the transcription factor to natural or synthetic DNA sequences. Furthermore, the in vitro measured binding affinities of a subset of oligonucleotides were found to correlate with their transcriptional activities in transfected cells. The combined computational-experimental approach exemplified in this work thus resulted in an accurate prediction method for CTF/NFI binding sites potentially functioning as regulatory regions in vivo.

Retinoic Acid Stimulation of the Human Surfactant Protein B Promoter Is Thyroid Transcription Factor 1 Site-dependent

Surfactant B (SP-B) is a 79-amino acid peptide critical to postnatal respiratory adaptation. Expression of SP-B by respiratory epithelial cells is regulated by developmental and hormonal influences at the level of gene transcription. Previous studies supported the role of retinoic acids (RA) and their receptors (RARs) in SP-B gene transcription. In the present study, RARalpha was detected in mouse alveolar type II epithelial cells where SP-B is synthesized and processed. Deletion and site-specific mutagenesis analysis identified clustered retinoic acid-responsive element sites in the 5'-flanking enhancer region of the hSP-B gene that bound RARalpha proteins. RAR coactivators ACTR, SRC-1, and transcriptional intermediary factor 2 (TIF2) stimulated human (h) SP-B promoter activity in a dose-dependent fashion in pulmonary adenocarcinoma H441 cells. In addition, an RAR-associated protein, CREB-binding protein (CBP), potentiated the effects of RAR on hSP-B promoter activity in H441 cells. Importantly, RA stimulation of the hSP-B promoter depends on tissue-specific thyroid transcription factor (TTF-1) DNA-binding sites. TTF-1 protein synergistically stimulated the hSP-B promoter with RARalpha, CBP, and nuclear receptor coactivators in H441 cells. In addition, TTF-1 interacted directly with RARalpha and TIF2 in the mammalian two-hybrid system. These findings support a model in which RAR/retinoid X receptor, TTF-1, coactivators, and CBP form a transcription activation complex in the upstream enhancer region of the hSP-B gene.

Isolation and Functional Characterization of the Mouse p75 TNF Receptor Promoter

Tumor necrosis factor (TNF) is a pleiotropic cytokine that plays an important role in immunological and inflammatory responses. It exerts its biological effects via two distinct membrane receptors of apparent molecular weight of 55 (p55TNFR) and 75 kDa (p75TNFR), respectively. Most cell lines and primary tissues express both receptor types. While the p55TNFR gene is constitutively expressed at rather low levels, the transcription of p75TNFR is strongly modulated by a number of stimulatory agents. To characterize the mouse p75TNFR gene expression on a molecular level, we screened a mouse genomic library using the 5′ end of the p75TNFR cDNA as a probe. A 6.3-kb genomic clone containing about 6 kb of 5′ flanking region and 300 bp of 3′ sequence including the translational start site and the first exon was isolated and subcloned. Primer extension analysis revealed three transcriptional start sites located at −35, −39, and −564 bp upstream of the ATG-containing first exon. To determine whether the 5′ flanking region exerts functional promoter activity, we generated deletion mutants fused to the luciferase reporter gene. Transfection of mouse fibroblasts (NIH3T3) with these constructs showed functional promoter activity of the isolated 5′ region. By further sequence analysis of the 5′ flanking region a number of putative DNA-binding sites for transcription factors, e.g., Sp1, CREB, Yi, YY1, and IFNγ-responsive element, were identified.

Autoactivation by a Candida glabrata copper metalloregulatory transcription factor requires critical minor groove interactions.

Rapid transcriptional autoactivation of the Candida glabrata AMT1 copper metalloregulatory transcription factor gene is essential for survival in the presence of high extracellular copper concentrations. Analysis of the interactions between purified recombinant AMT1 protein and the AMT1 promoter metal regulatory element was carried out by a combination of missing-nucleoside analysis, ethylation interference, site-directed mutagenesis, and quantitative in vitro DNA binding studies. The results of these experiments demonstrate that monomeric AMT1 binds the metal regulatory element with very high affinity and utilizes critical contacts in both the major and minor grooves. A single adenosine residue in the minor groove, conserved in all known yeast Cu metalloregulatory transcription factor DNA binding sites, plays a critical role in both AMT1 DNA binding in vitro and Cu-responsive AMT1 gene transcription in vivo. Furthermore, a mutation in the AMT1 Cu-activated DNA binding domain which converts a single arginine, found in a conserved minor groove binding domain, to lysine markedly reduces AMT1 DNA binding affinity in vitro and results in a severe defect in the ability of C. glabrata cells to mount a protective response against Cu toxicity.

Announcement

Tumor necrosis factor (TNF) is a pleiotropic cytokine that plays an important role in immunological and inflammatory responses. It exerts its biological effects via two distinct membrane receptors of apparent molecular weight of 55 (p55TNFR) and 75 kDa (p75TNFR), respectively. Most cell lines and primary tissues express both receptor types. While the p55TNFR gene is constitutively expressed at rather low levels, the transcription of p75TNFR is strongly modulated by a number of stimulatory agents. To characterize the mouse p75TNFR gene expression on a molecular level, we screened a mouse genomic library using the 5′ end of the p75TNFR cDNA as a probe. A 6.3-kb genomic clone containing about 6 kb of 5′ flanking region and 300 bp of 3′ sequence including the translational start site and the first exon was isolated and subcloned. Primer extension analysis revealed three transcriptional start sites located at −35, −39, and −564 bp upstream of the ATG-containing first exon. To determine whether the 5′ flanking region exerts functional promoter activity, we generated deletion mutants fused to the luciferase reporter gene. Transfection of mouse fibroblasts (NIH3T3) with these constructs showed functional promoter activity of the isolated 5′ region. By further sequence analysis of the 5′ flanking region a number of putative DNA-binding sites for transcription factors, e.g., Sp1, CREB, Yi, YY1, and IFNγ-responsive element, were identified.

21] Randomization and selection of RNA to identify targets for RRM RNA-binding proteins and antibodies

Publisher Summary The original peptide randomization experiments of Geysen were designed to identify antibody epitopes on plastic pins. This early approach, to generating combinatorial polymers, is similar in concept to the DNA randomization, selection, and polymerase chain reaction (PCR) amplification methods developed later, by Struhl and co-workers and Horwitz and Loeb, to identify the DNA-binding sites of transcription factors. Both of these in vitro selection methods required the ability to create high diversity of molecular sequences, by a randomization protocol, using synthetic polymers. The ability to amplify DNA libraries and binding ligands, selected from the libraries, by PCR, provided a distinct advantage over peptide libraries, because peptides had to be synthesized in a decodable (addressable) matrix. This limitation places severe practical constraints on the numbers of degenerate ligands that a peptide library can contain. On the other hand, the choice of 20 amino acids versus 4 nucleotides gives peptide libraries an exceedingly high potential for diversity compared to oligonucleotide libraries. The ability to determine sequence-binding preferences of proteins for RNAs, using randomization and selection, required the development of both RNA-binding methods and a means to identify the successful binding sequences. This chapter describes the RNA-binding assays as well as the methods to randomize RNA, to select the sequences for RNA-binding specificity, and to amplify selected RNAs, either in vivo, by DNA replication, or in vitro, using reverse transcription (RT)-PCR.