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/.

HTPSELEX--a database of high-throughput SELEX libraries for transcription factor binding sites.

HTPSELEX is a public database providing access to primary and derived data from high-throughput SELEX experiments aimed at characterizing the binding specificity of transcription factors. The resource is primarily intended to serve computational biologists interested in building models of transcription factor binding sites from large sets of binding sequences. The guiding principle is to make available all information that is relevant for this purpose. For each experiment, we try to provide accurate information about the protein material used, details of the wet lab protocol, an archive of sequencing trace files, assembled clone sequences (concatemers) and complete sets of in vitro selected protein-binding tags. In addition, we offer in-house derived binding sites models. HTPSELEX also offers reasonably large SELEX libraries obtained with conventional low-throughput protocols. The FTP site contains the trace archives and database flatfiles. The web server offers user-friendly interfaces for viewing individual entries and quality-controlled download of SELEX sequence libraries according to a user-defined sequencing quality threshold. HTPSELEX is available from ftp://ftp.isrec.isb-sib.ch/pub/databases/htpselex/ and http://www.isrec.isb-sib.ch/htpselex.

High-throughput SELEX SAGE method for quantitative modeling of transcription-factor binding sites.

The ability to determine the location and relative strength of all transcription-factor binding sites in a genome is important both for a comprehensive understanding of gene regulation and for effective promoter engineering in biotechnological applications. Here we present a bioinformatically driven experimental method to accurately define the DNA-binding sequence specificity of transcription factors. A generalized profile was used as a predictive quantitative model for binding sites, and its parameters were estimated from in vitro-selected ligands using standard hidden Markov model training algorithms. Computer simulations showed that several thousand low- to medium-affinity sequences are required to generate a profile of desired accuracy. To produce data on this scale, we applied high-throughput genomics methods to the biochemical problem addressed here. A method combining systematic evolution of ligands by exponential enrichment (SELEX) and serial analysis of gene expression (SAGE) protocols was coupled to an automated quality-controlled sequence extraction procedure based on Phred quality scores. This allowed the sequencing of a database of more than 10,000 potential DNA ligands for the CTF/NFI transcription factor. The resulting binding-site model defines the sequence specificity of this protein with a high degree of accuracy not achieved earlier and thereby makes it possible to identify previously unknown regulatory sequences in genomic DNA. A covariance analysis of the selected sites revealed non-independent base preferences at different nucleotide positions, providing insight into the binding mechanism.

Quantitative modelling of transcription factor binding sites

Abstract One of the most important issues in molecular biology is to understand regulatory mechanisms that control gene expression. Gene expression is often regulated by proteins, called transcription factors which bind to short (5 to 20 base pairs),degenerate segments of DNA. Experimental efforts towards understanding the sequence specificity of transcription factors is laborious and expensive, but can be substantially accelerated with the use of computational predictions. This thesis describes the use of algorithms and resources for transcriptionfactor binding site analysis in addressing quantitative modelling, where probabilitic models are built to represent binding properties of a transcription factor and can be used to find new functional binding sites in genomes. Initially, an open-access database(HTPSELEX) was created, holding high quality binding sequences for two eukaryotic families of transcription factors namely CTF/NF1 and LEFT/TCF. The binding sequences were elucidated using a recently described experimental procedure called HTP-SELEX, that allows generation of large number (> 1000) of binding sites using mass sequencing technology. For each HTP-SELEX experiments we also provide accurate primary experimental information about the protein material used, details of the wet lab protocol, an archive of sequencing trace files, and assembled clone sequences of binding sequences. The database also offers reasonably large SELEX libraries obtained with conventional low-throughput protocols.The database is available at http://wwwisrec.isb-sib.ch/htpselex/ and and ftp://ftp.isrec.isb-sib.ch/pub/databases/htpselex. The Expectation-Maximisation(EM) algorithm is one the frequently used methods to estimate probabilistic models to represent the sequence specificity of transcription factors. We present computer simulations in order to estimate the precision of EM estimated models as a function of data set parameters(like length of initial sequences, number of initial sequences, percentage of nonbinding sequences). We observed a remarkable robustness of the EM algorithm with regard to length of training sequences and the degree of contamination. The HTPSELEX database and the benchmarked results of the EM algorithm formed part of the foundation for the subsequent project, where a statistical framework called hidden Markov model has been developed to represent sequence specificity of the transcription factors CTF/NF1 and LEF1/TCF using the HTP-SELEX experiment data. The hidden Markov model framework is capable of both predicting and classifying CTF/NF1 and LEF1/TCF binding sites. A covariance analysis of the binding sites revealed non-independent base preferences at different nucleotide positions, providing insight into the binding mechanism. We next tested the LEF1/TCF model by computing binding scores for a set of LEF1/TCF binding sequences for which relative affinities were determined experimentally using non-linear regression. The predicted and experimentally determined binding affinities were in good correlation.

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.

Protein-binding site at the immunoglobulin mu membrane polyadenylylation signal: possible role in transcription termination.

mRNAs specifying immunoglobulin mu and delta heavy chains are encoded by a single large, complex transcription unit (mu + delta gene). The transcriptional activity of delta gene segments in terminally differentiated, IgM-secreting B lymphocytes is 10-20 times lower than in earlier B-lineage cells expressing delta mRNA. We find that transcription of the mu + delta gene in IgM-secreting murine myeloma cells terminates within a region of 500-1000 nucleotides immediately following the mu membrane (mu m) polyadenylylation site. Transcription decreases only minimally through this region in murine cell lines representative of earlier stages in B-cell development. A DNA fragment containing the mu m polyadenylylation signal gives protein-DNA complexes with different mobilities in gel retardation assays with nuclear extracts from myeloma cells than with nuclear extracts from earlier B-lineage cells. However, using a recently developed "footprinting" procedure in which protein-DNA complexes resolved in gel retardation assays are subjected to nucleolytic cleavage while still in the polyacrylamide gel, we find that the DNA sequences protected by factors from the two cell types are indistinguishable. The factor-binding site on the DNA is located 5' of the mu m polyadenylylation signal AATAAA and includes the 15-nucleotide-long A + T-rich palindrome CTGTAAACAAATGTC. This type of palindromic binding site exhibits orientation-dependent activity consistent with the reported properties of polymerase II termination signals. This binding site is followed by two sets of directly repeated DNA sequences with different helical conformation as revealed by their reactivity with the chemical nuclease 1,10-phenanthroline-copper. The close proximity of these features to the signals for mu m mRNA processing may reflect a linkage of the processes of developmentally regulated mu m polyadenylylation and transcription termination.

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.

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.