A new entropy model for RNA: part V, Incorporating the Flory-Huggins model in structure prediction and folding

The effect of solvent-biopolymer interactions is hardly negligible. Whereas the ideal (non-interacting) polymer consisting of N monomers in an ideal solvent is expected to have the terminal ends of its chain with a root-mean-squared (rms) end-to-end separation distance (<em>rms</em>) proportional to the square root of <em>N</em>, real interactions of a <em>rms</em> polymer both with itself and with the solvent often tend to strongly perturb <em>rms</em>. In <em>rms</em> poor solvent, the biopolymer can collapse into a small globule much smaller than the ideal <em>rms</em> due to excluding solvent. In good solvent, the biopolymer can swell to a size much larger than the ideal r due to favoring solvent. These effects require rms corrections to an ideal polymer equation. We have been developing the cross linking entropy (CLE) model in this series. The model attempts find the maximum entropy of a folded polymer by taking into account the correlation caused by bonding and other interactions of the structure. In RNA, this mostly occurs in the stems. Here we adapt CLE model to handle polymer swelling and collapse for RNA molecules both in good and in poor solvent. This work is intended to introduce this type of study and to allow its systematic application in problems of RNA folding and structure prediction. The current study suggests that there may be some tendency for RNA to behave as a polymer in poor solvent and that this collapse may happen in sequences longer than 50 nt.

A new entropy model for RNA: part IV, The Minimum Free Energy (mFE) and the thermodynamically most-probable folding pathway (TMPFP)

Here we discuss four important questions (1) how can we be sure that the thermodynamically most-probable folding-pathway yields the minimum free energy for secondary structure using the dynamic programming algorithm (DPA) approach, (2) what are its limitations, (3) how can we extend the DPA to find the minimum free energy with pseudoknots, and finally (4) what limitations can we expect to find in a DPA approach for pseudoknots. It is our supposition that some structures cannot be fit uniquely by the DPA, but may exist in real biology situations when disordered regions in the biomolecule are necessary. These regions would be identifiable by using suboptimal structure analysis. This grants us some qualitative tools to identify truly random RNA sequences, because such are likely to have greater degeneracy in their thermodynamically most-probable folding-pathway.

A new entropy model for RNA: part III. Is the folding free energy landscape of RNA funnel shaped?

The concept of a free energy (FE) landscape, in which the conformations of a polymer progressively take on the structure of the native state while spiraling down a FE surface that resembles the shape of a funnel, has long been viewed as the reason why a complex protein structure forms so rapidly compared to the number of conformations available to it. On the other hand, this landscape picture is less clear with RNA due to the multiplicity of conformations and the uncertainties in the current thermodynamics. It is therefore sometimes proposed that within the ensemble of suboptimal states of the RNA molecule, the vast majority of those states all closely resemble the native state and therefore simply overwhelm the few states that represent the global minimum FE. However, calculations of the free energy of observed structures often suggest that the most frequently observed cluster of structures are far from the minimum FE, particularly in the case of long sequences. If so, then such a FE surface is unlikely to be funnel shaped. We have been developing a version of <em>vsfold</em> that can evaluate the suboptimal structures of the FE surface (through a modified version called <em>vs_subopt</em>). Here we show that the ensemble of suboptimal structures for a number of known RNA structures can actually be both close to the minimum FE and also be the dominant observed structure when a proper Kuhn length is selected. Two state aptamers known as riboswitches can show neighboring FE states in the suboptimal structures that match the observed structures and their relative difference in FE is well within the range of the binding free energy of the metabolite. For the riboswitches and other short RNA sequences (less than 250 nt), the flow of the suboptimal structures (including pseudoknots) tended to resemble a rock rolling down a hill along the reaction coordinate axis. An important insight yielded by the cross-linking entropy (CLE) model is that the global entropy limits the size of domains. Hence, based on the CLE model, Levinthal’s paradox is overcome by the funnel shape in the FE, by a reduction in the number of degrees of freedom due to Kuhn length, and by limits on the size of the domains that can form. These concepts are also applicable to calculating transition rates between different suboptimal structures.

Practical strategies for the evaluation of high-affinity protein/nucleic acid interactions

The quantitative evaluation of binding interactions between proteins and nucleic acids is highly sensitive to a variety of experimental conditions. Optimization of these conditions is critical for obtaining high quality, reproducible data, particularly in the context of very high affinity interactions. Here, we discuss the practical considerations involved in optimizing the apparent binding constant of an interaction as measured by two common quantitative assays, electrophoretic mobility shift assay and double-filter binding when measuring extremely tight protein/nucleic acid interactions with sub-nanomolar binding affinities. We include specific examples from two telomere end-binding protein systems, <em>Schizosaccharomyces pombe</em> Pot1 and <em>Saccharomyces cerevisiae </em>Cdc13, to demonstrate potential experimental pitfalls and some useful strategies for optimization.

A new entropy model for RNA: part II. Persistence-related entropic contributions to RNA secondary structure free energy calculations

In previous work, we have shown that the entropy of a folded RNA molecule can be divided into local and global contributions using the cross-linking entropy (CLE) model, where, in the case of RNA, the cross- links are the base-pair stacking interactions. The local contribution to the CLE is revealed in the Kuhn length (a measure of the stiffness of the RNA). The Kuhn length acts as a scaling parameter. When the size of the system is rescaled, the relationship between local and global free energy must be renormalized to reflect this rescaling. In this renormalization process, the Kuhn length increases, the local entropy also increases due to freezing out of the local conformational degrees of freedom. At the same time, as the number of degrees of freedom decrease, there is a significant reduction in the global entropy. Here we present a method, based on the concepts of renormalization theory, to quantitatively estimate the size of the contribution from the local entropy as a function of the Kuhn length. The local entropy correction is used to predict the current empirically derived constant in the Jacobson-Stockmayer equation. The variation in the Kuhn length is shown to be largely influenced by the length of the double-stranded RNA stems formed in the secondary structure of folded RNA. This result is used to test the resulting entropy under a variable Kuhn length in stem-loop structures. Comparisons between a variable Kuhn length and a static Kuhn length on a short stem-loop of RNA are also examined. The model is quite general and is also directly applicable to protein structure and folding problems.

A modified Phenol-chloroform extraction method for isolating circulating cell free DNA of tumor patients

Searching for new cancer biomarkers, circulating cell-free DNA (cfDNA) has become an appealing target of interest as an elevated level of cfDNA has been detected in the circulation of cancer patients in comparison with healthy controls. Since cfDNA can be isolated from the circulation and other body fluids of patients without harming their physical condition, cfDNA is becoming a promising candidate as a novel non-invasive biomarker for cancer. The challenge in the diagnostic analysis of cfDNA is its very low presence in human plasma/serum and its partially strong fragmentation. Here we evaluated a modified phenol/chloroform extraction method for the isolation of cfDNA and compared it with published standard methods for cfDNA isolation.

A new entropy model for RNA: part I. A critique of the standard Jacobson-Stockmayer model applied to multiple cross links

The Jacobson-Stockmayer (JS) model is used in a number of standard programs for calculating the conformational entropy of RNA (and proteins). However, it is shown in this study that, in certain limiting cases, the current form of this model can lead to highly unphysical conclusions. The origin of this behavior can be traced to misunderstandings that occurred during the development of the model as applied to folded, single-stranded RNA. Here we show that an alternative model known as the cross linking entropy (CLE) model can overcome these issues. The principal object that causes entropy loss on a global scale in the CLE model is the <em>stem</em>, the primary measure of structural order in such coarse-grained calculations. The principal objects in the JS-model are various types of <em>loops</em>, and, with the exception of the hairpin loop, they are topologically local in character. To extract experimentally measurable variables, a simplified version of the CLE model is developed that resembles many features of the contact order model used in RNA and protein folding. These modifications are then applied to single molecule force-extension experiments (molecular tweezers) to extract quantitative information. It is further shown that a crude derivative of the CLE model itself can be derived directly from the JS-model when the misunderstandings are examined and corrected.

Computational prediction of candidate miRNAs and their targets from the completed Linum ussitatissimum genome and EST database

Flax is an important agronomic crop grown for its fiber (linen) and oil (linseed oil). In spite of many thousands of years of breeding some fiber varieties have been shown to rapidly respond to environmental stress with heritable changes to its genome. Many miRNAs appear to be induced by abiotic or biotic conditions experienced through the plant life cycle. Computational miRNA analysis of the flax genome provides a foundation for subsequent research on miRNA function in <em>Linum usitatissimum </em>and may also provide novel insight into any regulatory role the RNAi pathway may play in generating adaptive structural variation in response to environmental stress. Here a bioinformatics approach is used to screen for miRNAs previously identified in other plant species, as well as to predict putative miRNAs unique to a particular species which may not have been identified as they are less abundant or dependent upon a specific set of environmental conditions. Twelve miRNA genes were identified in flax on the basis of unique pre-miRNA positions with structural homology to plant pre-miRNAs and complete sequence homology to published plant miRNAs. These miRNAs were found to belong to 7 miRNA families, with an additional 2 matches corresponding to as yet unnamed poplar miRNAs and a parologous miRNA with partial sequence homology to mtr-miR4414b. An additional 649 novel and distinct flax miRNA genes were identified to form from canonical hairpin structures and to have putative targets among the ~30,000 flax Unigenes.

High mobility group A-interacting proteins in cancer: focus on chromobox protein homolog 7, homeodomain interacting protein kinase 2 and PATZ

The High Mobility Group A (HMGA) proteins, a family of DNA architectural factors, by interacting with different proteins play crucial roles in neoplastic transformation of a wide range of tissues. Therefore, the search for HMGA-interacting partners was carried out by several laboratories in order to investigate the mechanisms underlying HMGA-dependent tumorigenesis. Three of the several HMGA-binding proteins are discussed in this review. These are the Chromobox family protein (chromobox protein homolog 7, CBX7), the homeodomain interacting protein kinase 2 (HIPK2) and the POZ/domain and Kruppel zinc finger family member, PATZ. All of them play a critical role in tumorigenesis, and may also be independent markers of cancer. Their activities are linked to cell cycle, apoptosis and senescence. In this review, we discuss the properties of each protein, including their effect on HMGA1 functions, and propose a model accounting for how their activities might be coordinated.

The effect of in vitro exposure to antisense oligonucleotides on macrophage morphology and function

<p>Antisense oligonucleotides (AON) delivered via inhalation are in drug development for respiratory diseases. In rodents and monkeys, repeated exposure to high doses of inhaled phosphorothioate (PS) AON can lead to microscopic changes in the lungs, including accumulation of alveolar macrophages in the lower airway that have a <em>foamy</em> appearance. The functional consequences that result from this morphological change are unclear as there is controversy whether the vacuoles/inclusion bodies reflect normal clearance of the inhaled AON or are early indicators of lung toxicity. The morphological and functional responses of macrophage to PS AON were characterized <em>in vitro</em> using the comparator drug amiodarone, as a known inducer of foamy macrophages. Morphological changes of increased vacuolization with the presence of lamellated structures were observed in macrophages in response to both amiodarone and AON treatment. Functional responses to the drugs clearly differed with amiodarone treatment leading to apoptosis of cells and cell death, release of proinflammatory mediators IL-1RA, MIP-1<em>α </em>and TNF<em>α</em>, decrease in IP-10, a cytokine shown to be involved in protection against pulmonary fibrosis and altered phagocytosis capacity of the cells. In contrast, AON in concentrations up to 30 μM, had no effect on cell viability or apoptosis, had minimal effects on pro-inflammatory cytokines, increased IP-10 levels and did not alter the phagocytic capacity of the cells. Exposure of macrophages to AON<em> in vitro</em>, led to morphological changes of increased vacuolization, but did not lead to functional consequences which were observed with another vacuolization-inducing drug, suggesting that the <em>in vivo </em>phenotypic changes observed following inhalation of AON may be consistent with a clearance mechanism and not an activation or impairment of macrophages.</p>