Energetics of cooperative protein-DNA interactions: comparison between quantitative deoxyribonuclease footprint titration and filter binding

Using the binding of cI repressor protein to the lambda right and left operators as a model system, we have analyzed the two common experimental techniques for studying the interactions of genome regulatory proteins with multiple, specific sites on DNA. These are the quantitative DNase footprint titration technique [Brenowitz, M., Senear, D. F., Shea, M. A., & Ackers, G. K. (1986) Methods Enzymol. 130, 132-181] and the nitrocellulose filter binding assay [Riggs, A., Suzuki, H., & Bourgeois, S. (1970) J. Mol. Biol. 48, 67-83]. The footprint titration technique provides binding curves that separately represent the fractional saturation for each site. In principle, such data contain the information necessary to determine the thermodynamic constants for local site binding and cooperativity. We show that in practice, this is not possible for all values of the constants in multisite systems, such as the lambda operators. We show how these constants can nevertheless be uniquely determined by using additional binding data from a small number of mutant operators in which the number of binding sites has been reduced. The filter binding technique does not distinguish binding to the individual sites and yields only macroscopic binding parameters which are composite averages of the various local site and cooperativity constants. Moreover, the resolution of even macroscopic constants from filter binding data for multisite systems requires ad hoc assumptions as to a relationship between the number of ligands bound and the filter retention of the complex. Our results indicate that no such relationship exists. Hence, the technique does not permit determination of thermodynamically valid interaction constants (even macroscopic) in multisite systems.     

Making cool drugs hot: isothermal titration calorimetry as a tool to study binding energetics

Characterization of the thermodynamics of binding interactions is important in improving our understanding of bimolecular recognition and forms an essential part of the rational drug design process. Isothermal titration calorimetry (ITC) is rapidly becoming established as the method of choice for undertaking such studies. The power of ITC lies in its unique ability to measure binding reactions by the detection of the heat change during the binding interaction. Since heat changes occur during many physicochemical processes, ITC has a broad application, ranging from chemical and biochemical binding studies to more complex processes involving enthalpy changes, such as enzyme kinetics. Several features of ITC have facilitated its preferential use compared to other techniques that estimate affinity. It is a sensitive, rapid, and direct method with no requirement for chemical modification or immobilization. It is the only technique that directly measures enthalpy of binding and so eliminates the need for van't Hoff analysis, which can be time consuming and prone to uncertainty in parameter values. Although ITC has facilitated the measurement of the thermodynamics governing binding reactions, interpretation of these parameters in structural terms is still a major challenge.     

Native genomic blotting: a novel approach to mapping DNase I hypersensitive sites and protein-DNA interactions at high resolution

We have developed a new high resolution method for screening 400-600 base pairs of DNA in chromatin for DNase I hypersensitive sites and protein-DNA interactions. By separating the DNA isolated from nuclease-digested nuclei in small, native polyacrylamide gels prior to electroblotting onto nylon membranes, we increased the resolution by greater than 3-fold as compared with the traditional approach whereby the nuclease-digested DNA is fractionated electrophoretically in agarose gels (11). In addition, our native genomic blotting method has the advantage of combining the ability of the traditional agarose approach to detect DNase I hypersensitive sites, with the genomic sequencing method (2), where individual protein-DNA contacts can be observed. Native genomic blotting therefore permits for the first time the display of DNase I hypersensitive sites and protein-DNA interactions at high resolution on the same autoradiograph. This method allows us to investigate a new level of chromatin structure and to therefore obtain better insight into levels of gene structure, organization and gene regulation.     

FISH Finder: a high-throughput tool for analyzing FISH images

MOTIVATION: Fluorescence in situ hybridization (FISH) is used to study the organization and the positioning of specific DNA sequences within the cell nucleus. Analyzing the data from FISH images is a tedious process that invokes an element of subjectivity. Automated FISH image analysis offers savings in time as well as gaining the benefit of objective data analysis. While several FISH image analysis software tools have been developed, they often use a threshold-based segmentation algorithm for nucleus segmentation. As fluorescence signal intensities can vary significantly from experiment to experiment, from cell to cell, and within a cell, threshold-based segmentation is inflexible and often insufficient for automatic image analysis, leading to additional manual segmentation and potential subjective bias. To overcome these problems, we developed a graphical software tool called FISH Finder to automatically analyze FISH images that vary significantly. By posing the nucleus segmentation as a classification problem, compound Bayesian classifier is employed so that contextual information is utilized, resulting in reliable classification and boundary extraction. This makes it possible to analyze FISH images efficiently and objectively without adjustment of input parameters. Additionally, FISH Finder was designed to analyze the distances between differentially stained FISH probes. AVAILABILITY: FISH Finder is a standalone MATLAB application and platform independent software. The program is freely available from: http://code.google.com/p/fishfinder/downloads/list.     

Delta plots: a tool for analyzing phylogenetic distance data

A method is described that allows the assessment of treelikeness of phylogenetic distance data before tree estimation. This method is related to statistical geometry as introduced by Eigen, Winkler-Oswatitsch, and Dress (1988 [Proc. Natl. Acad. Sci. USA. 85:5913-5917]), and in essence, displays a measure for treelikeness of quartets in terms of a histogram that we call a delta plot. This allows identification of nontreelike data and analysis of noisy data sets arising from processes such as, for example, parallel evolution, recombination, or lateral gene transfer. In addition to an overall assessment of treelikeness, individual taxa can be ranked by reference to the treelikeness of the quartets to which they belong. Removal of taxa on the basis of this ranking results in an increase in accuracy of tree estimation. Recombinant data sets are simulated, and the method is shown to be capable of identifying single recombinant taxa on the basis of distance information alone, provided the parents of the recombinant sequence are sufficiently divergent and the mixture of tree histories is not strongly skewed toward a single tree. delta Plots and taxon rankings are applied to three biological data sets using distances derived from sequence alignment, gene order, and fragment length polymorphism.     

ConvAn: a convergence analyzing tool for optimization of biochemical networks

Dynamic models of biochemical networks usually are described as a system of nonlinear differential equations. In case of optimization of models for purpose of parameter estimation or design of new properties mainly numerical methods are used. That causes problems of optimization predictability as most of numerical optimization methods have stochastic properties and the convergence of the objective function to the global optimum is hardly predictable. Determination of suitable optimization method and necessary duration of optimization becomes critical in case of evaluation of high number of combinations of adjustable parameters or in case of large dynamic models. This task is complex due to variety of optimization methods, software tools and nonlinearity features of models in different parameter spaces. A software tool ConvAn is developed to analyze statistical properties of convergence dynamics for optimization runs with particular optimization method, model, software tool, set of optimization method parameters and number of adjustable parameters of the model. The convergence curves can be normalized automatically to enable comparison of different methods and models in the same scale. By the help of the biochemistry adapted graphical user interface of ConvAn it is possible to compare different optimization methods in terms of ability to find the global optima or values close to that as well as the necessary computational time to reach them. It is possible to estimate the optimization performance for different number of adjustable parameters. The functionality of ConvAn enables statistical assessment of necessary optimization time depending on the necessary optimization accuracy. Optimization methods, which are not suitable for a particular optimization task, can be rejected if they have poor repeatability or convergence properties. The software ConvAn is freely available on www.biosystems.lv/convan.     

miRspring: a compact standalone research tool for analyzing miRNA-seq data

High-throughput sequencing for microRNA (miRNA) profiling has revealed a vast complexity of miRNA processing variants, but these are difficult to discern for those without bioinformatics expertise and large computing capability. In this article, we present miRNA Sequence Profiling (miRspring) (http://mirspring.victorchang.edu.au), a software solution that creates a small portable research document that visualizes, calculates and reports on the complexities of miRNA processing. We designed an index-compression algorithm that allows the miRspring document to reproduce a complete miRNA sequence data set while retaining a small file size (typically <3 MB). Through analysis of 73 public data sets, we demonstrate miRspring’s features in assessing quality parameters, miRNA cluster expression levels and miRNA processing. Additionally, we report on a new class of miRNA variants, which we term seed-isomiRs, identified through the novel visualization tools of the miRspring document. Further investigation identified that ∼30% of human miRBase entries are likely to have a seed-isomiR. We believe that miRspring will be a highly useful research tool that will enhance the analysis of miRNA data sets and thus increase our understanding of miRNA biology.     

Ordination as a tool for analyzing complex data sets

Summary Ordination has proven to be a useful tool for examining relationships between environment and vegetation in data sets with a simple underlying environmental strueture. Complex data sets have proven much less tractable. A strategy is offered for dealing with complex data sets based on progressive removal of sets of stands along identified gradients, and subsequent reordination. This strategy is demonstrated using forests of the North Carolina piedmont.The author gratefully acknowledges the continuing collaboration of Dr. Norman L. Christensen of Duke University. This research was supported by National Science Foundation grants DEB-7708743 and DEB-7804043 to R.K.P. and DEB-7707532 and DEB-7804041 to N.L.C.     

Metastable secondary structures in ribosomal RNA: a new method for analyzing the titration behavior of rRNA

The pH titration behavior of E. coli rRNA in the acid range has been analyzed by combining spectrophotometric and potentiometric titration data. The “simplest” model for the system, which considers as possible reactions the protonation of adenine (A), cytosine (C), and guanine (G) residues along with the opening of A·U and G·C base pairs, does not adequately account for the titration properties. It is postulated that extra reactions may occur in addition to those in the “simplest” model, and a new analytical method was developed to deal with this situation. Our approach yields the ultraviolet spectral changes which accompany the extra reactions, from which the nature of these reactions can in principle be deduced. The calculations also give, at each pH, the extents of the extra reactions as well as the extents of those reactions which comprise the “simplest” model. We infer that in acidic RNA solutions of 0.1M ionic strength there occur at least two extra reactions, each of which involves G residues. We propose that in the pH range 6.0 ≥ pH ≥ 3.8 triple-stranded helical sequences, presumably protonated G·C·G, are formed. These regions are replaced at lower pH by acid-stable structures involving G·G and A·A base pairs. In solutions of lower ionic strength (I = 0.01M) no triple strands are formed, but G·G and A·A regions seem to develop even at pH values as high as 6.0. At I = 0.1M, an acid–base titration cycle between pH 7 and 2.8 is not reversible; rRNA shows true hysteresis behavior. We conclude that in ribosomal RNA's, which are generally G-rich, guanine residues may participate in hitherto unpredicted conformations, some of which may be metastable while others are equilibrium structures.     

Pi-pi interactions: the geometry and energetics of phenylalanine-phenylalanine interactions in proteins

The geometries of aromatic-aromatic interactions between phenylalanine residues in proteins are analysed in detail and correlated with energy calculations. A new definition of the interplanar angle is important for distinguishing favourable edge-to-face and unfavourable face-to-face orientations. The experimental observations are scattered over a wide range of conformational space, with no strongly preferred single orientation. However, Phe-Phe interactions occur almost exclusively in electrostatically attractive geometries: electrostatically unfavourable regions are only sparsely populated. Electrostatics dominate the geometry of interaction, while van der Waals' interactions are less significant, probably due to the hydrophobic environment of the protein core. The observations on proteins support the Hunter-Sanders rules for pi-pi interactions. In particular, offset stacked geometries, which theory predicts to be favourable, are observed experimentally. For monocyclic aromatics, use of a C-H dipole, the approach used in molecular mechanics calculations, accounts well for these aromatic-aromatic interactions. Comparison with the results obtained from the small molecules database indicates that the protein and small molecule crystal environments are very different.     

Structural basis for the energetics of jacalin-sugar interactions: promiscuity versus specificity

Jacalin, a tetrameric lectin, is one of the two lectins present in jackfruit (Artocarpus integrifolia) seeds. Its crystal structure revealed, for the first time, the occurrence of the beta-prism I fold in lectins. The structure led to the elucidation of the crucial role of a new N terminus generated by post-translational proteolysis for the lectin's specificity for galactose. Subsequent X-ray studies on other carbohydrate complexes showed that the extended binding site of jacalin consisted of, in addition to the primary binding site, a hydrophobic secondary site A composed of aromatic residues and a secondary site B involved mainly in water-bridges. A recent investigation involving surface plasmon resonance and the X-ray analysis of a methyl-alpha-mannose complex, had led to a suggestion of promiscuity in the lectin's sugar specificity. To explore this suggestion further, detailed isothermal titration calorimetric studies on the interaction of galactose (Gal), mannose (Man), glucose (Glc), Me-alpha-Gal, Me-alpha-Man, Me-alpha-Glc and other mono- and oligosaccharides of biological relevance and crystallographic studies on the jacalin-Me-alpha-Glc complex and a new form of the jacalin-Me-alpha-Man complex, have been carried out. The binding affinity of Me-alpha-Man is 20 times weaker than that of Me-alpha-Gal. The corresponding number is 27, when the binding affinities of Gal and Me-alpha-Gal, and those of Man and Me-alpha-Man are compared. Glucose (Glc) shows no measurable binding, while the binding affinity of Me-alpha-Glc is slightly less than that of Me-alpha-Man. The available crystal structures of jacalin-sugar complexes provide a convincing explanation for the energetics of binding in terms of interactions at the primary binding site and secondary site A. The other sugars used in calorimetric studies show no detectable binding to jacalin. These results and other available evidence suggest that jacalin is specific to O-glycans and its affinity to N-glycans is extremely weak or non-existent and therefore of limited value in processes involving biological recognition.     

An easy-to-use tool for planning and modeling a calorimetric titration

Isothermal titration calorimetry (ITC) is widely employed to measure thermodynamic properties of binding interactions between two macromolecules or a macromolecule and a small ligand. No labeling of interacting species is required for ITC, but this advantage is offset by potentially material-consuming experimental optimization complicated by an indirect readout of an ITC titration. Here we present a simple, practical, and portable spreadsheet-based tool for planning and modeling an ITC titration experiment accompanied by basic guidelines.