OligoWalk: an online siRNA design tool utilizing hybridization thermodynamics

Given an mRNA sequence as input, the OligoWalk web server generates a list of small interfering RNA (siRNA) candidate sequences, ranked by the probability of being efficient siRNA (silencing efficacy greater than 70%). To accomplish this, the server predicts the free energy changes of the hybridization of an siRNA to a target mRNA, considering both siRNA and mRNA self-structure. The free energy changes of the structures are rigorously calculated using a partition function calculation. By changing advanced options, the free energy changes can also be calculated using less rigorous lowest free energy structure or suboptimal structure prediction methods for the purpose of comparison. Considering the predicted free energy changes and local siRNA sequence features, the server selects efficient siRNA with high accuracy using a support vector machine. On average, the fraction of efficient siRNAs selected by the server that will be efficient at silencing is 78.6%. The OligoWalk web server is freely accessible through internet at http://rna.urmc.rochester.edu/servers/oligowalk

RNAi revised - Target mRNA-dependent enhancement of gene silencing

The discovery of RNA interference (RNAi) gave rise to the development of new nucleic acid-based technologies as powerful investigational tools and potential therapeutics. Mechanistic key details of RNAi in humans need to be deciphered yet, before such approaches take root in biomedicine and molecular therapy. We developed and validated an in silico-based model of siRNA-mediated RNAi in human cells in order to link in vitro-derived pre-steady state kinetic data with a quantitative and time-resolved understanding of RNAi on the cellular level. The observation that product release by Argonaute 2 is accelerated in the presence of an excess of target RNA in vitro inspired us to suggest an associative mechanism for the RNA slicer reaction where incoming target mRNAs actively promote dissociation of cleaved mRNA fragments. This novel associative model is compatible with highmultiple turnover rates of RNAibased gene silencing in living cells and accounts for target mRNA concentration-dependent enhancement of the RNAi machinery

Fundamental differences in the equilibrium considerations for siRNA and antisense oligodeoxynucleotide design

Both siRNA and antisense oligodeoxynucleotides (ODNs) inhibit the expression of a complementary gene. In this study, fundamental differences in the considerations for RNA interference and antisense ODNs are reported. In siRNA and antisense ODN databases, positive correlations are observed between the cost to open the mRNA target self-structure and the stability of the duplex to be formed, meaning the sites along the mRNA target with highest potential to form strong duplexes with antisense strands also have the greatest tendency to be involved in pre-existing structure. Efficient siRNA have less stable siRNA–target duplex stability than inefficient siRNA, but the opposite is true for antisense ODNs. It is, therefore, more difficult to avoid target self-structure in antisense ODN design. Self-structure stabilities of oligonucleotide and target correlate to the silencing efficacy of siRNA. Oligonucleotide self-structure correlations to efficacy of antisense ODNs, conversely, are insignificant. Furthermore, self-structure in the target appears to correlate with antisense ODN efficacy, but such that more effective antisense ODNs appear to target mRNA regions with greater self-structure. Therefore, different criteria are suggested for the design of efficient siRNA and antisense ODNs and the design of antisense ODNs is more challenging

HIV-1 RT-dependent DNAzyme expression inhibits HIV-1 replication without the emergence of escape viruses

DNAzymes are easier to prepare and less sensitive to chemical and enzymatic degradation than ribozymes; however, a DNA enzyme expression system has not yet been developed. In this study, we exploited the mechanism of HIV-1 reverse transcription (RT) in a DNA enzyme expression system. We constructed HIV-1 RT-dependent lentiviral DNAzyme expression vectors including the HIV-1 primer binding site, the DNA enzyme, and either a native tRNA (Lys-3), tRMDtRL, or one of two truncated tRNAs (Lys-3), tRMDΔARMtRL or tRMD3′-endtRL. Lentiviral vector-mediated DNAzyme expression showed high levels of inhibition of HIV-1 replication in SupT1 cells. We also demonstrated the usefulness of this approach in a long-term assay, in which we found that the DNAzymes prevented escape from inhibition of HIV. These results suggest that HIV-1 RT-dependent lentiviral vector-derived DNAzymes prevent the emergence of escape mutations

Strand antagonism in RNAi: an explanation of differences in potency between intracellularly expressed siRNA and shRNA

Strategies to regulate gene function frequently use small interfering RNAs (siRNAs) that can be made from their shRNA precursors via Dicer. However, when the duplex components of these siRNA effectors are expressed from their respective coding genes, the RNA interference (RNAi) activity is much reduced. Here, we explored the mechanisms of action of shRNA and siRNA and found the expressed siRNA, in contrast to short hairpin RNA (shRNA), exhibits strong strand antagonism, with the sense RNA negatively and unexpectedly regulating RNAi. Therefore, we altered the relative levels of strands of siRNA duplexes during their expression, increasing the level of the antisense component, reducing the level of the sense component, or both and, in this way we were able to enhance the potency of the siRNA. Such vector-delivered siRNA attacked its target effectively. These findings provide new insight into RNAi and, in particular, they demonstrate that strand antagonism is responsible for making siRNA far less potent than shRNA

A systematic analysis of the effect of target RNA structure on RNA interference

RNAi efficiency is influenced by local RNA structure of the target sequence. We studied this structure-based resistance in detail by targeting a perfect RNA hairpin and subsequently destabilized its tight structure by mutation, thereby gradually exposing the target sequence. Although the tightest RNA hairpins were completely resistant to RNAi, we observed an inverse correlation between the overall target hairpin stability and RNAi efficiency within a specific thermodynamic stability (ΔG) range. Increased RNAi efficiency was shown to be caused by improved binding of the siRNA to the destabilized target RNA hairpins. The mutational effects vary for different target regions. We find an accessible target 3′ end to be most important for RNAi-mediated inhibition. However, these 3′ end effects cannot be reproduced in siRNA-target RNA-binding studies in vitro, indicating the important role of RISC components in the in vivo RNAi reaction. The results provide a more detailed insight into the impact of target RNA structure on RNAi and we discuss several possible implications. With respect to lentiviral-mediated delivery of shRNA expression cassettes, we present a ΔG window to destabilize the shRNA insert for vector improvement, while avoiding RNAi-mediated self-targeting during lentiviral vector production

IntaRNA: efficient prediction of bacterial sRNA targets incorporating target site accessibility and seed regions

Motivation: During the last few years, several new small regulatory RNAs (sRNAs) have been discovered in bacteria. Most of them act as post-transcriptional regulators by base pairing to a target mRNA, causing translational repression or activation, or mRNA degradation. Numerous sRNAs have already been identified, but the number of experimentally verified targets is considerably lower. Consequently, computational target prediction is in great demand. Many existing target prediction programs neglect the accessibility of target sites and the existence of a seed, while other approaches are either specialized to certain types of RNAs or too slow for genome-wide searches

Cell stress is related to re-localization of Argonaute 2 and to decreased RNA interference in human cells

Various kinds of stress on human cells induce the formation of endogenous stress granules (SGs). Human Argonaute 2 (hAgo2), the catalytic core component of the RNA-induced silencing complex (RISC), can be recruited to SGs as well as P-bodies (PBs) indicating that the dynamic intracellular distribution of hAgo2 in SGs, in PBs or at other sub-cellular sites could be related to the efficiency of the RNA interference (RNAi) machinery. Here, we studied the influence of heat shock, sodium arsenite (NaAsO2), cycloheximide (CHX) and LipofectamineTM 2000-mediated transfection of phosphorothioate (PS)-modified oligonucleotides (ON) on the intracellular localization of hAgo2 and the efficiency of RNAi

Comparing Artificial Neural Networks, General Linear Models and Support Vector Machines in Building Predictive Models for Small Interfering RNAs

Exogenous short interfering RNAs (siRNAs) induce a gene knockdown effect in cells by interacting with naturally occurring RNA processing machinery. However not all siRNAs induce this effect equally. Several heterogeneous kinds of machine learning techniques and feature sets have been applied to modeling siRNAs and their abilities to induce knockdown. There is some growing agreement to which techniques produce maximally predictive models and yet there is little consensus for methods to compare among predictive models. Also, there are few comparative studies that address what the effect of choosing learning technique, feature set or cross validation approach has on finding and discriminating among predictive models.Three learning techniques were used to develop predictive models for effective siRNA sequences including Artificial Neural Networks (ANNs), General Linear Models (GLMs) and Support Vector Machines (SVMs). Five feature mapping methods were also used to generate models of siRNA activities. The 2 factors of learning technique and feature mapping were evaluated by complete 3x5 factorial ANOVA. Overall, both learning techniques and feature mapping contributed significantly to the observed variance in predictive models, but to differing degrees for precision and accuracy as well as across different kinds and levels of model cross-validation.The methods presented here provide a robust statistical framework to compare among models developed under distinct learning techniques and feature sets for siRNAs. Further comparisons among current or future modeling approaches should apply these or other suitable statistically equivalent methods to critically evaluate the performance of proposed models. ANN and GLM techniques tend to be more sensitive to the inclusion of noisy features, but the SVM technique is more robust under large numbers of features for measures of model precision and accuracy. Features found to result in maximally predictive models are not consistent across learning techniques, suggesting care should be taken in the interpretation of feature relevance. In the models developed here, there are statistically differentiable combinations of learning techniques and feature mapping methods where the SVM technique under a specific combination of features significantly outperforms all the best combinations of features within the ANN and GLM techniques

Small RNA interference-mediated gene silencing of heparanase abolishes the invasion, metastasis and angiogenesis of gastric cancer cells

<p>Abstract</p> <p>Background</p> <p>Heparanase facilitates the invasion and metastasis of cancer cells, and is over-expressed in many kinds of malignancies. Our studies indicated that heparanase was frequently expressed in advanced gastric cancers. The aim of this study is to determine whether silencing of heparanase expression can abolish the malignant characteristics of gastric cancer cells.</p> <p>Methods</p> <p>Three heparanase-specific small interfering RNA (siRNAs) were designed, synthesized, and transfected into cultured gastric cancer cell line SGC-7901. Heparanase expression was measured by RT-PCR, real-time quantitative PCR and Western blot. Cell proliferation was detected by MTT colorimetry and colony formation assay. The <it>in vitro </it>invasion and metastasis of cancer cells were measured by cell adhesion assay, scratch assay and matrigel invasion assay. The angiogenesis capabilities of cancer cells were measured by tube formation of endothelial cells.</p> <p>Results</p> <p>Transfection of siRNA against 1496-1514 bp of encoding regions resulted in reduced expression of heparanase, which started at 24 hrs and lasted for 120 hrs post-transfection. The siRNA-mediated silencing of heparanase suppressed the cellular proliferation of SGC-7901 cells. In addition, the <it>in vitro </it>invasion and metastasis of cancer cells were attenuated after knock-down of heparanase. Moreover, transfection of heparanase-specific siRNA attenuated the <it>in vitro </it>angiogenesis of cancer cells in a dose-dependent manner.</p> <p>Conclusions</p> <p>These results demonstrated that gene silencing of heparanase can efficiently abolish the proliferation, invasion, metastasis and angiogenesis of human gastric cancer cells <it>in vitro</it>, suggesting that heparanase-specific siRNA is of potential values as a novel therapeutic agent for human gastric cancer.</p