Modeling recursive RNA interference.

An important application of the RNA interference (RNAi) pathway is its use as a small RNA-based regulatory system commonly exploited to suppress expression of target genes to test their function in vivo. In several published experiments, RNAi has been used to inactivate components of the RNAi pathway itself, a procedure termed recursive RNAi in this report. The theoretical basis of recursive RNAi is unclear since the procedure could potentially be self-defeating, and in practice the effectiveness of recursive RNAi in published experiments is highly variable. A mathematical model for recursive RNAi was developed and used to investigate the range of conditions under which the procedure should be effective. The model predicts that the effectiveness of recursive RNAi is strongly dependent on the efficacy of RNAi at knocking down target gene expression. This efficacy is known to vary highly between different cell types, and comparison of the model predictions to published experimental data suggests that variation in RNAi efficacy may be the main cause of discrepancies between published recursive RNAi experiments in different organisms. The model suggests potential ways to optimize the effectiveness of recursive RNAi both for screening of RNAi components as well as for improved temporal control of gene expression in switch off-switch on experiments

A Novel Approach of Virotherapy Based Hsf-1 Shrna in Cancer Eradication

Cancer is the second leading cause of death worldwide with continues rise mortality rate. Current cancer treatment modalities are still ineffective and associated with many side effects leading to robust research to find new specific target therapy. Heat shock factor (HSF)-1 is heat shock response mediator protein and act as transcription factor for HSP encoding gene. Many cancers have up-regulated HSP as a result of increase HSF-1 expression. Interestingly, inhibition of HSF-1 has no effect to normal cell, indicating HSF-1 as promises target therapy. RNAi is potential mechanism to block and down regulate HSF-1 which will affect many cellular processes in cancer cell. Combining RNAi base treatment with oncolityc viruses will boost the therapeutic effect of this novel treatment. Despite its potency, this modality still need further research in order to evaluate its efficacy and optimal doses to gain optimal result

An accurate and interpretable model for siRNA efficacy prediction

BACKGROUND: The use of exogenous small interfering RNAs (siRNAs) for gene silencing has quickly become a widespread molecular tool providing a powerful means for gene functional study and new drug target identification. Although considerable progress has been made recently in understanding how the RNAi pathway mediates gene silencing, the design of potent siRNAs remains challenging. RESULTS: We propose a simple linear model combining basic features of siRNA sequences for siRNA efficacy prediction. Trained and tested on a large dataset of siRNA sequences made recently available, it performs as well as more complex state-of-the-art models in terms of potency prediction accuracy, with the advantage of being directly interpretable. The analysis of this linear model allows us to detect and quantify the effect of nucleotide preferences at particular positions, including previously known and new observations. We also detect and quantify a strong propensity of potent siRNAs to contain short asymmetric motifs in their sequence, and show that, surprisingly, these motifs alone contain at least as much relevant information for potency prediction as the nucleotide preferences for particular positions. CONCLUSION: The model proposed for prediction of siRNA potency is as accurate as a state-of-the-art nonlinear model and is easily interpretable in terms of biological features. It is freely available on the web a

The South American fruit fly : an important pest insect with RNAi-sensitive larval stages

RNA interference (RNAi) technology has been used in the development of approaches for pest control. The presence of some essential genes, the so-called "core genes," in the RNAi machinery is crucial for its efficiency and robust response in gene silencing. Thus, our study was designed to examine whether the RNAi machinery is functional in the South American (SA) fruit fly Anastrepha fraterculus (Diptera: Tephritidae) and whether the sensitivity to the uptake of double-stranded RNA (dsRNA) could generate an RNAi response in this fruit fly species. To prepare a transcriptome database of the SA fruit fly, total RNA was extracted from all the life stages for later cDNA synthesis and Illumine sequencing. After the de novo transcriptome assembly and gene annotation, the transcriptome was screened for RNAi pathway genes, as well as the duplication or loss of genes and novel target genes to dsRNA delivery bioassays. The dsRNA delivery assay by soaking was performed in larvae to evaluate the gene-silencing of V-ATPase, and the upregulation of Dicer-2 and Argonaute-2 after dsRNA delivery was analyzed to verify the activation of siRNAi machinery. We tested the stability of dsRNA using dsGFP with an in vitro incubation of larvae body fluid (hemolymph). We identified 55 genes related to the RNAi machinery with duplication and loss for some genes and selected 143 different target genes related to biological processes involved in postembryonic growth/development and reproduction of A. fraterculus. Larvae soaked in dsRNA (dsV-ATPase) solution showed a strong knockdown of V-ATPase after 48 h, and the expression of Dicer-2 and Argonaute-2 responded with an increase upon the exposure to dsRNA. Our data demonstrated the existence of a functional RNAi machinery in the SA fruit fly, and we present an easy and robust physiological bioassay with the larval stages that can further be used for screening of target genes at in vivo organisms' level for RNAi-based control of fruit fly pests. This is the first study that provides evidence of a functional siRNA machinery in the SA fruit fly

Integrated siRNA design based on surveying of features associated with high RNAi effectiveness

BACKGROUND: Short interfering RNAs have allowed the development of clean and easily regulated methods for disruption of gene expression. However, while these methods continue to grow in popularity, designing effective siRNA experiments can be challenging. The various existing siRNA design guidelines suffer from two problems: they differ considerably from each other, and they produce high levels of false-positive predictions when tested on data of independent origins. RESULTS: Using a distinctly large set of siRNA efficacy data assembled from a vast diversity of origins (the siRecords data, containing records of 3,277 siRNA experiments targeting 1,518 genes, derived from 1,417 independent studies), we conducted extensive analyses of all known features that have been implicated in increasing RNAi effectiveness. A number of features having positive impacts on siRNA efficacy were identified. By performing quantitative analyses on cooperative effects among these features, then applying a disjunctive rule merging (DRM) algorithm, we developed a bundle of siRNA design rule sets with the false positive problem well curbed. A comparison with 15 online siRNA design tools indicated that some of the rule sets we developed surpassed all of these design tools commonly used in siRNA design practice in positive predictive values (PPVs). CONCLUSION: The availability of the large and diverse siRNA dataset from siRecords and the approach we describe in this report have allowed the development of highly effective and generally applicable siRNA design rule sets. Together with ever improving RNAi lab techniques, these design rule sets are expected to make siRNAs a more useful tool for molecular genetics, functional genomics, and drug discovery studies

Management of pest insects and plant diseases by non-transformative RNAi

Since the discovery of RNA interference (RNAi), scientists have made significant progress towards the development of this unique technology for crop protection. The RNAi mechanism works at the mRNA level by exploiting a sequence-dependent mode of action with high target specificity due to the design of complementary dsRNA molecules, allowing growers to target pests more precisely compared to conventional agrochemicals. The delivery of RNAi through transgenic plants is now a reality with some products currently in the market. Conversely, it is also expected that more RNA-based products reach the market as non-transformative alternatives. For instance, topically applied dsRNA/siRNA (SIGS - Spray Induced Gene Silencing) has attracted attention due to its feasibility and low cost compared to transgenic plants. Once on the leaf surface, dsRNAs can move directly to target pest cells (e.g., insects or pathogens) or can be taken up indirectly by plant cells to then be transferred into the pest cells. Water-soluble formulations containing pesticidal dsRNA provide alternatives, especially in some cases where plant transformation is not possible or takes years and cost millions to be developed (e.g., perennial crops). The ever-growing understanding of the RNAi mechanism and its limitations has allowed scientists to develop non-transgenic approaches such as trunk injection, soaking, and irrigation. While the technology has been considered promising for pest management, some issues such as RNAi efficiency, dsRNA degradation, environmental risk assessments, and resistance evolution still need to be addressed. Here, our main goal is to review some possible strategies for non-transgenic delivery systems, addressing important issues related to the use of this technology

Programmable biomaterials for dynamic and responsive drug delivery

Biomaterials are continually being designed that enable new methods for interacting dynamically with cell and tissues, in turn unlocking new capabilities in areas ranging from drug delivery to regenerative medicine. In this review, we explore some of the recent advances being made in regards to programming biomaterials for improved drug delivery, with a focus on cancer and infection. We begin by explaining several of the underlying concepts that are being used to design this new wave of drug delivery vehicles, followed by examining recent materials systems that are able to coordinate the temporal delivery of multiple therapeutics, dynamically respond to changing tissue environments, and reprogram their bioactivity over time

Bio-inspired pulmonary surfactant-modified nanogels : a promising siRNA delivery system

Inhalation therapy with small interfering RNA (siRNA) is a promising approach in the treatment of pulmonary disorders. However, clinical translation is severely limited by the lack of suitable delivery platforms. In this study, we aim to address this limitation by designing a novel bioinspired hybrid nanoparticle with a core-shell nanoarchitecture, consisting of a siRNA-loaded dextran nanogel (siNG) core and a pulmonary surfactant (Curosurf (R)) outer shell. The decoration of siNGs with a surfactant shell enhances the colloidal stability and prevents siRNA release in the presence of competing polyanions, which are abundantly present in biofluids. Additionally, the impact of the surfactant shell on the biological efficacy of the siNGs is determined in lung cancer cells. The presence of the surfactants substantially reduces the cellular uptake of siNGs. Remarkably, the lowered intracellular dose does not impede the gene silencing effect, suggesting a crucial role of the pulmonary surfactant in the intracellular processing of the nanoparticles. In order to surmount the observed reduction in cellular dose, folate is incorporated as a targeting ligand in the pulmonary surfactant shell to incite receptor-mediated endocytosis. The latter substantially enhances both cellular uptake and gene silencing potential, achieving efficient knockdown at siRNA concentrations in the low nanomolar range. (C) 2015 Elsevier B.V. All rights reserved

Designing of highly effective complementary and mismatch siRNAs for silencing a gene

In past, numerous methods have been developed for predicting efficacy of short interfering RNA (siRNA). However these methods have been developed for predicting efficacy of fully complementary siRNA against a gene. Best of author's knowledge no method has been developed for predicting efficacy of mismatch siRNA against a gene. In this study, a systematic attempt has been made to identify highly effective complementary as well as mismatch siRNAs for silencing a gene. Support vector machine (SVM) based models have been developed for predicting efficacy of siRNAs using composition, binary and hybrid pattern siRNAs. We achieved maximum correlation 0.67 between predicted and actual efficacy of siRNAs using hybrid model. All models were trained and tested on a dataset of 2182 siRNAs and performance was evaluated using five-fold cross validation techniques. The performance of our method desiRm is comparable to other well-known methods. In this study, first time attempt has been made to design mutant siRNAs (mismatch siRNAs). In this approach we mutated a given siRNA on all possible sites/positions with all possible nucleotides. Efficacy of each mutated siRNA is predicted using our method desiRm. It is well known from literature that mismatches between siRNA and target affects the silencing efficacy. Thus we have incorporated the rules derived from base mismatches experimental data to find out over all efficacy of mutated or mismatch siRNAs. Finally we developed a webserver, desiRm (http://www.imtech.res.in/raghava/desirm/) for designing highly effective siRNA for silencing a gene. This tool will be helpful to design siRNA to degrade disease isoform of heterozygous single nucleotide polymorphism gene without depleting the wild type protein

Design of RNAi reagents for invertebrate model organisms and human disease vectors

RNAi has become an important tool to silence gene expression in a variety of organisms, in particular when classical genetic methods are missing. However, application of this method in functional studies has raised new challenges in the design of RNAi reagents in order to minimize false positive and false negative results. Since the performance of reagents can be rarely validated on a genome-wide scale, improved computational methods are required that consider experimentally derived design parameters. Here, we describe computational methods for the design of RNAi reagents for invertebrate model organisms and human disease vectors, such as Anopheles. We describe procedures on how to design short and long double-stranded RNAs for single genes, and evaluate their predicted specificity and efficiency. Using a bioinformatics pipeline we also describe how to design a genome-wide RNAi library for Anopheles gambiae