Transcription factor-DNA Complexes Research Articles

A sticky-end probe biosensor for homogeneous detection of transcription factor binding activity.

Transcription factors are essential regulators of various physiological and pathological processes. However, detecting transcription factor-DNA binding activities is often time-consuming and labor-intensive. Homogeneous biosensors that are compatible with mix-and-measure protocols have the potential to simplify the workflow for therapeutic screening and disease diagnostics. In this study, we apply a combined computational-experimental approach to investigate the design of a sticky-end probe biosensor, where the transcription factor-DNA complex stabilizes the fluorescence resonance energy transfer signal of the donor-acceptor pair. We design a sticky-end biosensor for the SOX9 transcription factor based on the consensus sequence and characterize its sensing performance. A systems biology model is also developed to investigate the reaction kinetics and optimize the operating conditions. Taken together, our study provides a conceptual framework for the design and optimization of sticky-end probe biosensors for homogeneous detection of transcription factor-DNA binding activity.

Characterization of a Salmonella Transcription Factor-DNA Complex and Identification of the Inducer by Native Mass Spectrometry

FraR, a transcriptional repressor, was postulated to regulate the metabolism of the Amadori compound fructose-asparagine (F-Asn) in the foodborne pathogen Salmonella enterica. Here, the DNA- and inducer-binding affinities and stoichiometries of FraR were determined and cross-validated by electrophoretic mobility-shift assays (EMSAs) and online buffer exchange coupled to native mass spectrometry (OBE-nMS). We demonstrate the utility of OBE-nMS to characterize protein and protein-DNA complexes that are not amenable to offline exchange into volatile buffers. OBE-nMS complemented EMSAs by revealing that FraR binds to the operator DNA as a dimer and by establishing 6-phosphofructose-aspartate as the inducer that weakens DNA binding by FraR. These results provide insights into how FraR regulates the expression of F-Asn-catabolizing enzymes and add to our understanding of the intricate bacterial circuitry that dictates utilization of diverse nutrients.

Corepressors in CD4+ T cell development and homeostasis

Abstract Corepressors NCOR1 and NCOR2/SMRT serve as scaffolds for the recruitment of histone deacetylases to transcription factor-DNA complexes. These closely related proteins are functionally non-redundant. Though they were first identified by their interactions with nuclear receptors, NCOR1/2 also interact with non-nuclear receptor transcription factors, including several involved in T cell development and polarization. Previous research identified that NCOR1 promotes survival of double positive thymocytes and protects them from negative selection. We have built upon this work by examining the effect of combined NCOR1/2 deletion in developing thymocytes. NCOR1/2 deletion using a CD4-Cre model results in an 8-fold decrease in the frequency of CD4 single positive T cells, compared to a 2-fold decrease and an insignificant decrease for NCOR1 and NCOR2 deletion alone, respectively. NCOR1/2-deficient T cells demonstrate exquisite sensitivity to TCR stimulation and polarize to Th subsets at different frequencies compared to wild-type CD4+ T cells. Despite a profound loss of CD4 single positive T cells and thymic regulatory T cells (Tregs), the frequency of both Treg progenitor populations remains unchanged. In contrast, the frequency of splenic Tregs is not reduced in NCOR1/2-deficient mice. However, there is a striking increase in activation of conventional T cells, suggesting that T cell tolerance is perturbed. Using an OX40-Cre deletion model which deletes NCOR1/2 in dendritic cells (DCs), activated T cells, and Tregs, we observe a decreased CD4+/CD8+ ratio and high incidence of ulcerative dermatitis. We are currently examining how Treg or DC specific deletion of NCOR1/2 affects T cell development, homeostasis, and tolerance.

An SVM-based method for assessment of transcription factor-DNA complex models

BackgroundAtomic details of protein-DNA complexes can provide insightful information for better understanding of the function and binding specificity of DNA binding proteins. In addition to experimental methods for solving protein-DNA complex structures, protein-DNA docking can be used to predict native or near-native complex models. A docking program typically generates a large number of complex conformations and predicts the complex model(s) based on interaction energies between protein and DNA. However, the prediction accuracy is hampered by current approaches to model assessment, especially when docking simulations fail to produce any near-native models.ResultsWe present here a Support Vector Machine (SVM)-based approach for quality assessment of the predicted transcription factor (TF)-DNA complex models. Besides a knowledge-based protein-DNA interaction potential DDNA3, we applied several structural features that have been shown to play important roles in binding specificity between transcription factors and DNA molecules to quality assessment of complex models. To address the issue of unbalanced positive and negative cases in the training dataset, we applied hard-negative mining, an iterative training process that selects an initial training dataset by combining all of the positive cases and a random sample from the negative cases. Results show that the SVM model greatly improves prediction accuracy (84.2%) over two knowledge-based protein-DNA interaction potentials, orientation potential (60.8%) and DDNA3 (68.4%). The improvement is achieved through reducing the number of false positive predictions, especially for the hard docking cases, in which a docking algorithm fails to produce any near-native complex models.ConclusionsA learning-based SVM scoring model with structural features for specific protein-DNA binding and an atomic-level protein-DNA interaction potential DDNA3 significantly improves prediction accuracy of complex models by successfully identifying cases without near-native structural models.

Molecular spectroscopic and thermodynamic studies on the interaction of anti-platelet drug ticlopidine with calf thymus DNA

Ticlopidine is an anti-platelet drug which belongs to the thienopyridine structural family and exerts its effect by functioning as an ADP receptor inhibitor. Ticlopidine inhibits the expression of TarO gene in S. aureus and may provide protection against MRSA. Groove binding agents are known to disrupt the transcription factor DNA complex and consequently inhibit gene expression. Understanding the mechanism of interaction of ticlopidine with DNA can prove useful in the development of a rational drug designing system. At present, there is no such study on the interaction of anti-platelet drugs with nucleic acids. A series of biophysical experiments were performed to ascertain the binding mode between ticlopidine and calf thymus DNA. UV–visible and fluorescence spectroscopic experiments confirmed the formation of a complex between ticlopidine and calf thymus DNA. Moreover, the values of binding constant were found to be in the range of 103M−1, which is indicative of groove binding between ticlopidine and calf thymus DNA. These results were further confirmed by studying the effect of denaturation on double stranded DNA, iodide quenching, viscometric studies, thermal melting profile as well as CD spectral analysis. The thermodynamic profile of the interaction was also determined using isothermal titration calorimetric studies. The reaction was found to be endothermic and the parameters obtained were found to be consistent with those of known groove binders. In silico molecular docking studies further corroborated well with the experimental results.

Protein-DNA interfaces: a molecular dynamics analysis of time-dependent recognition processes for three transcription factors.

We have studied the dynamics of three transcription factor–DNA complexes using all-atom, microsecond-scale MD simulations. In each case, the salt bridges and hydrogen bond interactions formed at the protein–DNA interface are found to be dynamic, with lifetimes typically in the range of tens to hundreds of picoseconds, although some interactions, notably those involving specific binding to DNA bases, can be a hundred times longer lived. Depending on the complex studied, this dynamics may or may not lead to the existence of distinct conformational substates. Using a sequence threading technique, it has been possible to determine whether DNA sequence recognition is sensitive or not to such conformational changes, and, in one case, to show that recognition appears to be locally dependent on protein-mediated cation distributions.

Imino proton NMR guides the reprogramming of A•T specific minor groove binders for mixed base pair recognition.

Sequence-specific binding to DNA is crucial for targeting transcription factor-DNA complexes to modulate gene expression. The heterocyclic diamidine, DB2277, specifically recognizes a single G•C base pair in the minor groove of mixed base pair sequences of the type AAAGTTT. NMR spectroscopy reveals the presence of major and minor species of the bound compound. To understand the principles that determine the binding affinity and orientation in mixed sequences of DNA, over thirty DNA hairpin substrates were examined by NMR and thermal melting. The NMR exchange dynamics between major and minor species shows that the exchange is much faster than compound dissociation determined from biosensor–surface plasmon resonance. Extensive modifications of DNA sequences resulted in a unique DNA sequence with binding site AAGATA that binds DB2277 in a single orientation. A molecular docking result agrees with the model representing rapid flipping of DB2277 between major and minor species. Imino spectral analysis of a 15N-labeled central G clearly shows the crucial role of the exocyclic amino group of G in sequence-specific recognition. Our results suggest that this approach can be expanded to additional modules for recognition of more sequence-specific DNA complexes. This approach provides substantial information about the sequence-specific, highly efficient, dynamic nature of minor groove binding agents.

27 Analysis of DNA deformations in transcription factor–DNA complexes

Interactions between proteins and DNA are a key component of fundamental biological processes such as transcriptional regulation. DNA bending and other deformations are commonly observed in experim...

The underlying molecular and network level mechanisms in the evolution of robustness in gene regulatory networks.

Gene regulatory networks show robustness to perturbations. Previous works identified robustness as an emergent property of gene network evolution but the underlying molecular mechanisms are poorly understood. We used a multi-tier modeling approach that integrates molecular sequence and structure information with network architecture and population dynamics. Structural models of transcription factor-DNA complexes are used to estimate relative binding specificities. In this model, mutations in the DNA cause changes on two levels: (a) at the sequence level in individual binding sites (modulating binding specificity), and (b) at the network level (creating and destroying binding sites). We used this model to dissect the underlying mechanisms responsible for the evolution of robustness in gene regulatory networks. Results suggest that in sparse architectures (represented by short promoters), a mixture of local-sequence and network-architecture level changes are exploited. At the local-sequence level, robustness evolves by decreasing the probabilities of both the destruction of existent and generation of new binding sites. Meanwhile, in highly interconnected architectures (represented by long promoters), robustness evolves almost entirely via network level changes, deleting and creating binding sites that modify the network architecture.

TFinDit: transcription factor-DNA interaction data depository

BackgroundOne of the crucial steps in regulation of gene expression is the binding of transcription factor(s) to specific DNA sequences. Knowledge of the binding affinity and specificity at a structural level between transcription factors and their target sites has important implications in our understanding of the mechanism of gene regulation. Due to their unique functions and binding specificity, there is a need for a transcription factor-specific, structure-based database and corresponding web service to facilitate structural bioinformatics studies of transcription factor-DNA interactions, such as development of knowledge-based interaction potential, transcription factor-DNA docking, binding induced conformational changes, and the thermodynamics of protein-DNA interactions.DescriptionTFinDit is a relational database and a web search tool for studying transcription factor-DNA interactions. The database contains annotated transcription factor-DNA complex structures and related data, such as unbound protein structures, thermodynamic data, and binding sequences for the corresponding transcription factors in the complex structures. TFinDit also provides a user-friendly interface and allows users to either query individual entries or generate datasets through culling the database based on one or more search criteria.ConclusionsTFinDit is a specialized structural database with annotated transcription factor-DNA complex structures and other preprocessed data. We believe that this database/web service can facilitate the development and testing of TF-DNA interaction potentials and TF-DNA docking algorithms, and the study of protein-DNA recognition mechanisms.

Benchmarks for flexible and rigid transcription factor-DNA docking

BackgroundStructural insight from transcription factor-DNA (TF-DNA) complexes is of paramount importance to our understanding of the affinity and specificity of TF-DNA interaction, and to the development of structure-based prediction of TF binding sites. Yet the majority of the TF-DNA complexes remain unsolved despite the considerable experimental efforts being made. Computational docking represents a promising alternative to bridge the gap. To facilitate the study of TF-DNA docking, carefully designed benchmarks are needed for performance evaluation and identification of the strengths and weaknesses of docking algorithms.ResultsWe constructed two benchmarks for flexible and rigid TF-DNA docking respectively using a unified non-redundant set of 38 test cases. The test cases encompass diverse fold families and are classified into easy and hard groups with respect to the degrees of difficulty in TF-DNA docking. The major parameters used to classify expected docking difficulty in flexible docking are the conformational differences between bound and unbound TFs and the interaction strength between TFs and DNA. For rigid docking in which the starting structure is a bound TF conformation, only interaction strength is considered.ConclusionsWe believe these benchmarks are important for the development of better interaction potentials and TF-DNA docking algorithms, which bears important implications to structure-based prediction of transcription factor binding sites and drug design.

Computational modeling on the recognition of the HRE motif by HIF-1: molecular docking and molecular dynamics studies

Hypoxia inducible factor-1 (HIF-1) is a bHLH-family transcription factor that controls genes involved in glycolysis, angiogenesis, migration, as well as invasion factors that are important for tumor progression and metastasis. HIF-1, a heterodimer of HIF-1α and HIF-1β, binds to the hypoxia responsive element (HRE) present in the promoter regions of hypoxia responsive genes, such as vascular endothelial growth factor (VEGF). Neither the structure of free HIF-1 nor that of its complex with HRE is available. Computational modeling of the transcription factor-DNA complex has always been challenging due to their inherent flexibility and large conformational space. The present study aims to model the interaction between the DNA-binding domain of HIF-1 and HRE. Experiments showed that rigid macromolecular docking programs (HEX and GRAMM-X) failed to predict the optimal dimerization of individually modeled HIF-1 subunits. Hence, the HIF-1 heterodimer was modeled based on the phosphate system positive regulatory protein (PHO4) homodimer. The duplex VEGF-DNA segment containing HRE with flanking nucleotides was modeled in the B form and equilibrated via molecular dynamics (MD) simulation. A rigid docking approach was used to predict the crude binding mode of HIF-1 dimer with HRE, in which the putative contacts were found to be present. An MD simulation (5 ns) of the HIF-1-HRE complex in explicit water was performed to account for its flexibility and to optimize its interactions. All of the conserved amino acid residues were found to play roles in the recognition of HRE. The present work, which sheds light on the recognition of HRE by HIF-1, could be beneficial in the design of peptide or small molecule therapeutics that can mimic HIF-1 and bind with the HRE sequence.

A ubiquitin-selective AAA-ATPase mediates transcriptional switching by remodelling a repressor–promoter DNA complex

Switches between different phenotypes and their underlying states of gene transcription occur as cells respond to intrinsic developmental cues or adapt to changing environmental conditions. Post-translational modification of the master regulatory transcription factors that define the initial phenotype is a common strategy to direct such transitions. Emerging evidence indicates that the modification of key transcription factors by the small polypeptide ubiquitin plays a central role in many of these transitions1, 2. However, the molecular mechanisms by which ubiquitination regulates the switching of promoters between active and inactive states are largely unknown. Ubiquitination of the yeast transcriptional repressor α2 is necessary to evoke the transition between mating-types3, and here, we dissected the impact of this modification on α2 dynamics at its target promoters. The ubiquitination of α2 does not alter DNA occupancy by depleting the existing pool of the transcription factor, despite its well-characterized function in directing repressor turnover. Rather, α2 ubiquitination plays a direct role in the rapid removal of the repressor from its DNA targets. This disassembly of α2 from DNA depends on the ubiquitin-selective AAA-ATPase Cdc48. Our findings expand the functional targets of Cdc48 to active transcriptional regulatory complexes in the nucleus, a far broader role than previously anticipated. These data reveal an ubiquitin-dependent extraction pathway for dismantling transcription factor-DNA complexes and provide an archetype for the regulation of transcriptional switching events by ubiquitination.

Structure‐based prediction of transcription factor binding sites using a protein‐DNA docking approach

Accurate identification of transcription factor binding sites is critical to our understanding of transcriptional regulatory networks. To overcome the issue of high false-positive predictions that trouble the sequence-based prediction techniques, we have developed a structure-based prediction method that takes into consideration of interactions between the amino acids of a transcription factor and the nucleotides of its DNA binding sequence at structural level, along with an efficient protein-DNA docking algorithm. The docked structures between a protein and a DNA are evaluated using a knowledge-based energy function, in conjunction with van der Waals energy. Our docking algorithm supports quasi-flexible docking, overcoming a number of limiting issues faced by similar docking algorithms. Our rigid-body docking algorithm is tested on a dataset of 141 nonredundant transcription factor-DNA complex structures. The test results show that 63.1% of the 141 complex structures are reconstructed with accuracies better than 1.0 A RMSDs (root mean square deviation) and 79.4% of the complexes are predicted with accuracies better than 3.0 A RMSDs when using the native DNA structures. Our quasi-flexible docking algorithm, assuming that the DNA structures are not known, is tested on a separate set of 45 transcription factor-DNA complexes, of which 57.8% of the docked complex conformations achieve better than 1.0 A RMSDs while 71.1% of the complexes have RMSDs less than 3.0 A. We have also applied our method to predict the binding motifs of the ferric uptake regulator in E. coli and showed that most of the experimentally identified sites can be predicted accurately.

Phosphorylation of the Gal4 DNA-binding domain is essential for activator mono-ubiquitylation and efficient promoter occupancy.

Recent analysis of a Gal4 mutant (Gap71) carrying three point mutations (S22D, K23Q and K25F) in its DNA-binding domain (DBD), has demonstrated that it cannot occupy GAL promoters efficiently in cells and that it is not mono-ubiquitylated, suggesting a functional link between this modification and stable DNA binding in cells. The mechanistic underpinning of this phenotype is that this protein is hypersensitive to a newly discovered activity of the proteasomal ATPases--their ability to actively dissociate transcription factor-DNA complexes after direct interaction with the activation domain. In this paper, we examine the roles of each of the three point mutations contained in Gap71 individually. These experiments have revealed that serine 22 is a site of phosphorylation in the Gal4 DBD and that lysine 23 is essential for S22 phosphorylation, possibly acting as part of the kinase recognition site. Mutation of either residue blocks Gal4 DBD phosphorylation, its subsequent ubiquitylation and compromises the ability of the activator to bind promoter DNA in vivo. These data represent the first report of an essential phosphorylation event that is critical for the activity of this paradigmatic transcription factor.

Position dependencies in transcription factor binding sites

Most of the available tools for transcription factor binding site prediction are based on methods which assume no sequence dependence between the binding site base positions. Our primary objective was to investigate the statistical basis for either a claim of dependence or independence, to determine whether such a claim is generally true, and to use the resulting data to develop improved scoring functions for binding-site prediction. Using three statistical tests, we analyzed the number of binding sites showing dependent positions. We analyzed transcription factor-DNA crystal structures for evidence of position dependence. Our final conclusions were that some factors show evidence of dependencies whereas others do not. We observed that the conformational energy (Z-score) of the transcription factor-DNA complexes was lower (better) for sequences that showed dependency than for those that did not (P < 0.02). We suggest that where evidence exists for dependencies, these should be modeled to improve binding-site predictions. However, when no significant dependency is found, this correction should be omitted. This may be done by converting any existing scoring function which assumes independence into a form which includes a dependency correction. We present an example of such an algorithm and its implementation as a web tool. http://promoterplot.fmi.ch/cgi-bin/dep.html

Replication fork blockage by transcription factor-DNA complexes in Escherichia coli

All organisms require mechanisms that resuscitate replication forks when they break down, reflecting the complex intracellular environments within which DNA replication occurs. Here we show that as few as three lac repressor-operator complexes block Escherichia coli replication forks in vitro regardless of the topological state of the DNA. Blockage with tandem repressor-operator complexes was also observed in vivo, demonstrating that replisomes have a limited ability to translocate through high affinity protein–DNA complexes. However, cells could tolerate tandem repressor-bound operators within the chromosome that were sufficient to block all forks in vitro. This discrepancy between in vitro and in vivo observations was at least partly explained by the ability of RecA, RecBCD and RecG to abrogate the effects of repressor-operator complexes on cell viability. However, neither RuvABC nor RecF were needed for normal cell growth in the face of such complexes. Holliday junction resolution by RuvABC and facilitated loading of RecA by RecF were not therefore critical for tolerance of protein–DNA blocks. We conclude that there is a trade-off between efficient genome duplication and other aspects of DNA metabolism such as transcriptional control, and that recombination enzymes, either directly or indirectly, provide the means to tolerate such conflicts.

Associations and Interactions between Ets-1 and Ets-2 and Coregulatory Proteins, SRC-1, AIB1, and NCoR in Breast Cancer

Associations between p160 coactivator proteins and the development of resistance to endocrine treatment have been described. We hypothesized that nuclear receptor coregulatory proteins may interact with nonsteroid receptors. We investigated the mitogen-activated protein kinase-activated transcription factors, Ets, as possible interaction proteins for the coactivators SRC-1 and AIB1 and the corepressor NCoR in human breast cancer. Expression and coexpression of Ets and the coregulatory proteins was investigated using immunohistochemistry and immunofluorescence in a cohort of breast tumor patients (N = 134). Protein expression, protein-DNA interactions and protein-protein interactions were assessed using Western blot, electromobility shift, and coimmunoprecipitation analysis, respectively. Ets-1 and Ets-2 associated with reduced disease-free survival (P < 0.0292, P < 0.0001, respectively), whereas NCoR was a positive prognostic indicator (P < 0.0297). Up-regulation of Ets-1 protein expression in cell cultures derived from patient tumors in the presence of growth factors associated with tumor grade (P < 0.0013; n = 28). In primary breast tumor cell cultures and in the SKBR3 breast cell line, growth factors induced interaction between Ets and their DNA response element, induced recruitment of coactivators to the transcription factor-DNA complex, and up-regulated protein expression of HER2. Ets-1 and Ets-2 interacted with the coregulators under basal conditions, and growth factors up-regulated Ets-2 interaction with SRC-1 and AIB1. Coexpression of Ets-2 and SRC-1 significantly associated with the rate of recurrence and HER expression, compared with patients who expressed Ets-2 but not SRC-1 (P < 0.0001 and P < 0.0001, respectively). These data describe associations and interactions between nonsteroid transcription factors and coregulatory proteins in human breast cancer.

Analysis of a repressor region in the human neuropeptide Y gene that binds Oct-1 and Pbx-1 in GT1-7 neurons

The mechanisms dictating the developmental expression of individual neuropeptides within the hypothalamus have not yet been elucidated. In this paper we have studied the cis-acting elements involved in the repression of neuropeptide Y (NPY) gene expression in a gonadotropin-releasing hormone (GnRH) neuronal cell model, GT1-7 cells. Using transient transfection of the human NPY 5 ′ regulatory region into the GT1-7 neurons, we have found a repressor region located between −867 and −1078. DNase I footprint analysis of this region revealed three specific protein binding elements. Further analysis of the region between −942 and −922 bp using electrophoretic mobility shift assays revealed that four different transcription factor-DNA complexes form with GT1-7 nuclear proteins, whereas only three complexes are detected using baby hamster kidney (BHK) cell nuclear extract. Mutation of the consensus binding sequence abolishes all complex formation on the −924/−922 oligonucleotide. Antibody supershift assays revealed that Oct-1 and Pbx-1 antibodies were able to eliminate the appearance of two specific complexes. Therefore we suggest that this region may be important for transcriptional repression of the NPY gene in a heterologous cell model, through complex, coordinate protein–protein interactions.

Inhibition of transcription factor-DNA complexes and gene expression by a microgonotropen.

Developing minor groove-binding drugs to selectively inhibit transcription factor (TF)/DNA interactions and accompanying gene expression is a current goal in drug development studies. Equipping minor groove-binding agents with positively charged, major groove-contacting side chains yields microgonotropens (MGTs). Previously, we demonstrated that MGTs were superior inhibitors of TF/DNA complexes in cell-free assays compared with "classical" groove binders, but MGTs showed limited ability to inhibit gene expression. To determine what chemical characteristics contribute to or improve activity, we evaluate five MGTs for their effectiveness in inhibiting TF complex formation and resultant transcription by using the c-fos serum response element (SRE) as a target. MGT L1 binds DNA via a bisbenzimidazole equipped with a tripyrrole moiety. It is compared with analog L2, which has been functionalized with propylamines on each of the three pyrroles. L2, which binds DNA at subpicomolar concentrations, was at least three orders of magnitude more potent than L1 at inhibiting TF binding to the c-fos SRE in cell-free assays. Unlike L1 and previous MGTs, L2 also inhibited endogenous c-fos expression in NIH 3T3 cells at micromolar levels. Structure/activity relationships suggest that, although the tripyrrole/polyamine functional group of L2 may be largely responsible for its inhibition of TF complexes in cell-free assays, its bisbenzimidazole moiety appears to impart improved cellular uptake and activity. These findings make L2 a promising lead candidate for future, rational MGT design.