rSNP_Guide, a database system for analysis of transcription factor binding to target sequences: application to SNPs and site-directed mutations

rSNP_Guide is a novel curated database system for analysis of transcription factor (TF) binding to target sequences in regulatory gene regions altered by mutations. It accumulates experimental data on naturally occurring site variants in regulatory gene regions and site-directed mutations. This database system also contains the web tools for SNP analysis, i.e., active applet applying weight matrices to predict the regulatory site candidates altered by a mutation. The current version of the rSNP_Guide is supplemented by six sub-databases: (i) rSNP_DB, on DNA–protein interaction caused by mutation; (ii) SYSTEM, on experimental systems; (iii) rSNP_BIB, on citations to original publications; (iv) SAMPLES, on experimentally identified sequences of known regulatory sites; (v) MATRIX, on weight matrices of known TF sites; (vi) rSNP_Report, on characteristic examples of successful rSNP_Tools implementation. These databases are useful for the analysis of natural SNPs and site-directed mutations. The databases are available through the Web, http://wwwmgs.bionet.nsc.ru/mgs/systems/rsnp/.

Phylogenetic footprinting of transcription factor binding sites in proteobacterial genomes

Toward the goal of identifying complete sets of transcription factor (TF)-binding sites in the genomes of several gamma proteobacteria, and hence describing their transcription regulatory networks, we present a phylogenetic footprinting method for identifying these sites. Probable transcription regulatory sites upstream of Escherichia coli genes were identified by cross-species comparison using an extended Gibbs sampling algorithm. Close examination of a study set of 184 genes with documented transcription regulatory sites revealed that when orthologous data were available from at least two other gamma proteobacterial species, 81% of our predictions corresponded with the documented sites, and 67% corresponded when data from only one other species were available. That the remaining predictions included bona fide TF-binding sites was proven by affinity purification of a putative transcription factor (YijC) bound to such a site upstream of the fabA gene. Predicted regulatory sites for 2097 E.coli genes are available at http://www.wadsworth.org/resnres/bioinfo/.

Multiplex selection technique (MuST): an approach to clone transcription factor binding sites.

We have used a multiplex selection approach to construct a library of DNA-protein interaction sites recognized by many of the DNA-binding proteins present in a cell type. An estimated minimum of two-thirds of the binding sites present in a library prepared from activated Jurkat T cells represent authentic transcription factor binding sites. We used the library for isolation of "optimal" binding site probes that facilitated cloning of a factor and to identify binding activities induced within 2 hr of activation of Jurkat cells. Since a large fraction of the oligonucleotides obtained appear to represent "optimal" binding sites for sequence-specific DNA-binding proteins, it is feasible to construct a catalog of consensus binding sites for DNA-binding proteins in a given cell type. Qualitative and quantitative comparisons of the catalogs of binding site sequences from various cell types could provide valuable insights into the process of differentiation acting at the level of transcriptional control.

Genomic regions harboring insecticide resistance-associated Cyp genes are enriched by transposable element fragments carrying putative transcription factor binding sites in two sibling Drosophila species

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

CIITA stimulation of transcription factor binding to major histocompatibility complex class II and associated promoters in vivo

CIITA is a master transactivator of the major histocompatibility complex class II genes, which are involved in antigen presentation. Defects in CIITA result in fatal immunodeficiencies. CIITA activation is also the control point for the induction of major histocompatibility complex class II and associated genes by interferon-γ, but CIITA does not bind directly to DNA. Expression of CIITA in G3A cells, which lack endogenous CIITA, followed by in vivo genomic footprinting, now reveals that CIITA is required for the assembly of transcription factor complexes on the promoters of this gene family, including DRA, Ii, and DMB. CIITA-dependent promoter assembly occurs in interferon-γ-inducible cell types, but not in B lymphocytes. Dissection of the CIITA protein indicates that transactivation and promoter loading are inseparable and reveal a requirement for a GTP binding motif. These findings suggest that CIITA may be a new class of transactivator.

Assessing computational tools for the discovery of transcription factor binding sites

The prediction of regulatory elements is a problem where computational methods offer great hope. Over the past few years, numerous tools have become available for this task. The purpose of the current assessment is twofold: to provide some guidance to users regarding the accuracy of currently available tools in various settings, and to provide a benchmark of data sets for assessing future tools.

Interaction between Candida albicans and Pseudomonas aeruginosa

Fungal pathogen Candida albicans causes serious nosocomial infections in patients, in part, due to formation of drug-resistant biofilms. Protein kinases (PK) and transcription factors (TF) mediate signal transduction and transcription of proteins involved in biofilm development. To discover biofilm-related PKs, a collection of 63 C. albicans PK mutants was screened twice independently with microtiter plate-based biofilm assay (XTT). Thirty-eight (60%) mutants showed different degrees of biofilm impairment with the poor biofilm formers additionally possessing filamentation defects. Most of these genes were already known to encode proteins associated with Candida morphology and biofilms but VPS15, PKH3, PGA43, IME2 and CEX1, were firstly associated with both processes in this study. Previous studies of Holcombe et al. (2010) had shown that bacterial pathogen, Pseudomonas aeruginosa can impair C. albicans filamentation and biofilm development. To investigate their interaction, the good biofilm former PK mutants of C. albicans were assessed for their response to P. aeruginosa supernatants derived from two strains, wildtype PAO1 and homoserine lactone (HSL)-free mutant ΔQS, without finding any nonresponsive mutants. This suggested that none of the PKs in this study was implicated in Candida-Pseudomonas signaling. To screen promoter sequences for overrepresented TFs across C. albicans gene sets significantly up/downregulated in presence of bacterial supernatants from Holcombe et al. (2010) study, TFbsST database was created online. The TFbsST database integrates experimentally verified TFs of Candida to analyse promoter sequences for TF binding sites. In silico studies predicted that Efg1p was overrepresented in C. albicans and C. parapsilosis RBT family genes.

Regulation of chromatin structure, Smad binding and AFP expression by the Forkhead box transcription factor: Foxa1

Transcription factors must be able to access their DNA binding sites to either activate or repress transcription. However, DNA wrapping and compaction into chromatin occludes most binding sites from ready access by proteins. Pioneer transcription factors are capable of binding their DNA elements within a condensed chromatin context and then reducing the level of nucleosome occupancy so that the chromatin structure is more accessible. This altered accessibility increases the probability of other transcription factors binding to their own DNA binding elements. My hypothesis is that Foxa1, a ‘pioneer’ transcription factor, activates alpha-fetoprotein (AFP) expression by binding DNA in a chromatinized environment, reducing the nucleosome occupancy and facilitating binding of additional transcription factors.^ Using retinoic-acid differentiated mouse embryonic stem cells, we illustrate a mechanism for activation of the tumor marker AFP by the pioneer transcription factor Foxa1 and TGF-β downstream effector transcription factors Smad2 and Smad4. In differentiating embryonic stem cells, binding of the Foxa1 forkhead box transcription factor to chromatin reduces nucleosome occupancy and levels of linker histone H1 at the AFP distal promoter. The more accessible DNA is subsequently bound by the Smad2 and Smad4 transcription factors, concurrent with activation of transcription. Chromatin immunoprecipitation analyses combined with siRNA-mediated knockdown indicate that Smad protein binding and the reduction of nucleosome occupancy at the AFP distal promoter is dependent on Foxa1. In addition to facilitating transcription factor binding, Foxa1 is also associated with histone modifications related to active gene expression. Acetylation of lysine 9 on histone H3, a mark that is associated active transcription, is dependent on Foxa1, while methylation of H3K4, also associated with active transcription, is independent of Foxa1. I propose that Foxa1 potentiates a region of chromatin to respond to Smad proteins, leading to active expression of AFP.^ These studies demonstrate one mechanism whereby a transcription factor can alter the accessibility of additional transcription factors to chromatin, by altering nucleosome positions. Specifically, Foxa1 exposes DNA so that Smad4 can bind to its regulatory element and activate transcription of the tumor-marker gene AFP.^

MRG1, the product of a melanocyte-specific gene related gene, is a cytokine-inducible transcription factor with transformation activity

Identification of cytokine-inducible genes is imperative for determining the mechanisms of cytokine action. A cytokine-inducible gene, mrg1 [melanocyte-specific gene (msg1) related gene], was identified through mRNA differential display of interleukin (IL) 9-stimulated and unstimulated mouse helper T cells. In addition to IL-9, mrg1 can be induced by other cytokines and biological stimuli, including IL-1α, -2, -4, -6, and -11, granulocyte/macrophage colony-stimulating factor, interferon γ, platelet-derived growth factor, insulin, serum, and lipopolysaccharide in diverse cell types. The induction of mrg1 by these stimuli appears to be transient, with induction kinetics similar to other primary response genes, implicating its role in diverse biological processes. Deletion or point mutations of either the Box1 motif (binds Janus kinase 1) or the signal transducer and activator of transcription 3 binding site-containing region within the intracellular domain of the IL-9 receptor ligand binding subunit abolished or greatly reduced mrg1 induction by IL-9, suggesting that the Janus kinase/signal transducer and activator of transcription signaling pathway is required for mrg1 induction, at least in response to IL-9. Transfection of mrg1 cDNA into TS1, an IL-9-dependent mouse T cell line, converted these cells to IL-9-independent growth through a nonautocrine mechanism. Overexpression of mrg1 in Rat1 cells resulted in loss of cell contact inhibition, anchorage-independent growth in soft agar, and tumor formation in nude mice, demonstrating that mrg1 is a transforming gene. MRG1 is a transcriptional activator and may represent a founding member of an additional family of transcription factors.

Chromatin accessibility mapping identifies mediators of basal transcription and retinoid-induced repression of OTX2 in medulloblastoma.

Despite an emerging understanding of the genetic alterations giving rise to various tumors, the mechanisms whereby most oncogenes are overexpressed remain unclear. Here we have utilized an integrated approach of genomewide regulatory element mapping via DNase-seq followed by conventional reporter assays and transcription factor binding site discovery to characterize the transcriptional regulation of the medulloblastoma oncogene Orthodenticle Homeobox 2 (OTX2). Through these studies we have revealed that OTX2 is differentially regulated in medulloblastoma at the level of chromatin accessibility, which is in part mediated by DNA methylation. In cell lines exhibiting chromatin accessibility of OTX2 regulatory regions, we found that autoregulation maintains OTX2 expression. Comparison of medulloblastoma regulatory elements with those of the developing brain reveals that these tumors engage a developmental regulatory program to drive OTX2 transcription. Finally, we have identified a transcriptional regulatory element mediating retinoid-induced OTX2 repression in these tumors. This work characterizes for the first time the mechanisms of OTX2 overexpression in medulloblastoma. Furthermore, this study establishes proof of principle for applying ENCODE datasets towards the characterization of upstream trans-acting factors mediating expression of individual genes.

Sequence-selective carbohydrate-DNA interaction: dimeric and monomeric forms of the calicheamicin oligosaccharide interfere with transcription factor function.

The synthetic oligosaccharide moiety of the antibiotic calicheamicin and the head-to-head dimer of this oligosaccharide are known to bind to the minor groove of DNA in a sequence-selective manner preferring distinct target sequences. We tested these carbohydrates for their ability to interfere with transcription factor function. The oligosaccharides inhibit binding of transcription factors to DNA in a sequence-selective manner, probably by inducing a conformational change in DNA structure. They also interfere with transcription by polymerase II in vitro. The effective concentrations of the oligosaccharides for inhibition of transcription factor binding and for transcriptional inhibition are in the micromolar range. The dimer is a significantly more active inhibitor than is the monomer.

The porcine circovirus type 1 capsid gene promoter improves antigen expression and immunogenicity in a HIV-1 plasmid vaccine

Background. One of the promising avenues for development of vaccines against Human immunodeficiency virus type 1 (HIV-1) and other human pathogens is the use of plasmid-based DNA vaccines. However, relatively large doses of plasmid must be injected for a relatively weak response. We investigated whether genome elements from Porcine circovirus type 1 (PCV-1), an apathogenic small ssDNA-containing virus, had useful expression-enhancing properties that could allow dose-sparing in a plasmid vaccine. Results. The linearised PCV-1 genome inserted 5' of the CMV promoter in the well-characterised HIV-1 plasmid vaccine pTHgrttnC increased expression of the polyantigen up to 2-fold, and elicited 3-fold higher CTL responses in mice at 10-fold lower doses than unmodified pTHgrttnC. The PCV-1 capsid gene promoter (Pcap) alone was equally effective. Enhancing activity was traced to a putative composite host transcription factor binding site and a "Conserved Late Element" transcription-enhancing sequence previously unidentified in circoviruses. Conclusions. We identified a novel PCV-1 genome-derived enhancer sequence that significantly increased antigen expression from plasmids in in vitro assays, and improved immunogenicity in mice of the HIV-1 subtype C vaccine plasmid, pTHgrttnC. This should allow significant dose sparing of, or increased responses to, this and other plasmid-based vaccines. We also report investigations of the potential of other circovirus-derived sequences to be similarly used. © 2011 Tanzer et al; licensee BioMed Central Ltd.

Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach

Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.