DSIR: assessing the design of highly potent siRNA by testing a set of cancer-relevant target genes

Coalescent RNA-localizing and transcriptional activities of SAM68 modulate adhesion and subendothelial basement membrane assembly

Endothelial cell interactions with their extracellular matrix are essential for vascular homeostasis and expansion. Large-scale proteomic analyses aimed at identifying components of integrin adhesion complexes have revealed the presence of several RNA binding proteins (RBPs) of which the functions at these sites remain poorly understood. Here, we explored the role of the RBP SAM68 (Src associated in mitosis, of 68 kDa) in endothelial cells. We found that SAM68 is transiently localized at the edge of spreading cells where it participates in membrane protrusive activity and the conversion of nascent adhesions to mechanically loaded focal adhesions by modulation of integrin signaling and local delivery of β-actin mRNA. Furthermore, SAM68 depletion impacts cell-matrix interactions and motility through induction of key matrix genes involved in vascular matrix assembly. In a 3D environment SAM68-dependent functions in both tip and stalk cells contribute to the process of sprouting angiogenesis. Altogether, our results identify the RBP SAM68 as a novel actor in the dynamic regulation of blood vessel networks.

A polycistronic transgene design for combinatorial genetic perturbations from a single transcript in Drosophila

Experimental models that capture the genetic complexity of human disease and allow mechanistic explorations of the underlying cell, tissue, and organ interactions are crucial to furthering our understanding of disease biology. Such models require combinatorial manipulations of multiple genes, often in more than one tissue at once. The ability to perform complex genetic manipulations in vivo is a key strength of Drosophila, where many tools for sophisticated and orthogonal genetic perturbations exist. However, combining the large number of transgenes required to establish more representative disease models and conducting mechanistic studies in these already complex genetic backgrounds is challenging. Here we present a design that pushes the limits of Drosophila genetics by allowing targeted combinatorial ectopic expression and knockdown of multiple genes from a single inducible transgene. The polycistronic transcript encoded by this transgene includes a synthetic short hairpin cluster cloned within an intron placed at the 5' end of the transcript, followed by two protein-coding sequences separated by the T2A sequence that mediates ribosome skipping. This technology is particularly useful for modeling genetically complex diseases like cancer, which typically involve concurrent activation of multiple oncogenes and loss of multiple tumor suppressors. Furthermore, consolidating multiple genetic perturbations into a single transgene further streamlines the ability to perform combinatorial genetic manipulations and makes it readily adaptable to a broad palette of transgenic systems. This flexible design for combinatorial genetic perturbations will also be a valuable tool for functionally exploring multigenic gene signatures identified from omics studies of human disease and creating humanized Drosophila models to characterize disease-associated variants in human genes. It can also be adapted for studying biological processes underlying normal tissue homeostasis and development that require simultaneous manipulation of many genes.

Antiviral efficacy of short-hairpin RNAs and artificial microRNAs targeting foot-and-mouth disease virus

RNA interference (RNAi) is a well-conserved mechanism in eukaryotic cells that directs post-transcriptional gene silencing through small RNA molecules. RNAi has been proposed as an alternative approach for rapid and specific control of viruses including foot-and-mouth disease virus (FMDV), the causative agent of a devastating animal disease with high economic impact. The aim of this work was to assess the antiviral activity of different small RNA shuttles targeting the FMDV RNA-dependent RNA polymerase coding sequence (3D). Three target sequences were predicted within 3D considering RNA accessibility as a major criterion. The silencing efficacy of short-hairpin RNAs (shRNAs) and artificial microRNAs (amiRNAs) targeting the selected sequences was confirmed in fluorescent reporter assays. Furthermore, BHK-21 cells transiently expressing shRNAs or amiRNAs proved 70 to >95% inhibition of FMDV growth. Interestingly, dual expression of amiRNAs did not improve FMDV silencing. Lastly, stable cell lines constitutively expressing amiRNAs were established and characterized in terms of antiviral activity against FMDV. As expected, viral replication in these cell lines was delayed. These results show that the target RNA-accessibility-guided approach for RNAi design rendered efficient amiRNAs that constrain FMDV replication. The application of amiRNAs to complement FMDV vaccination in specific epidemiological scenarios shall be explored further.

Searching for a Putative Mechanism of RIZ2 Tumor-Promoting Function in Cancer Models

Positive Regulatory Domain (PRDM) gene family members commonly express two main molecular variants, the PR-plus isoform usually acting as tumor suppressor and the PR-minus one functioning as oncogene. Accordingly, PRDM2/RIZ encodes for RIZ1 (PR-plus) and RIZ2 (PR-minus). In human cancers, genetic or epigenetic modifications induce RIZ1 silencing with an expression level imbalance in favor of RIZ2 that could be relevant for tumorigenesis. Additionally, in estrogen target cells and tissues, estradiol increases RIZ2 expression level with concurrent increase of cell proliferation and survival. Several attempts to study RIZ2 function in HeLa or MCF-7 cells by its over-expression were unsuccessful. Thus, we over-expressed RIZ2 in HEK-293 cells, which are both RIZ1 and RIZ2 positive but unresponsive to estrogens. The forced RIZ2 expression increased cell viability and growth, prompted the G2-to-M phase transition and organoids formation. Accordingly, microarray analysis revealed that RIZ2 regulates several genes involved in mitosis. Consistently, RIZ silencing in both estrogen-responsive MCF-7 and -unresponsive MDA-MB-231 cells induced a reduction of cell proliferation and an increase of apoptosis rate. Our findings add novel insights on the putative RIZ2 tumor-promoting functions, although additional attempts are warranted to depict the underlying molecular mechanism.

Antisense drug discovery and development technology considered in a pharmacological context

When coined, the term "antisense" included oligonucleotides of any structure, with any chemical modification and designed to work through any post-RNA hybridization mechanism. However, in practice the term "antisense" has been used to describe single stranded oligonucleotides (ss ASOs) designed to hybridize to RNAswhile the term "siRNA" has come to mean double stranded oligonucleotides designed to activate Ago2. However, the two approaches share many common features. The medicinal chemistry developed for ASOs greatly facilitated the development of siRNA technology and remains the chemical basis for both approaches. Many of challenges faced and solutions achieved share many common features. In fact, because ss ASOs can be designed to activate Ago2, the two approaches intersect at this remarkably important protein. There are also meaningful differences. The pharmacokinetic properties are quite different and thus potential routes of delivery differ. ASOs may be designedto use a variety of post-RNA binding mechanismswhile siRNAs depend solely on the robust activity of Ago2. However, siRNAs and ASOs are both used for therapeutic purposes and both must be and can be understood in a pharmacological context. Thus, the goals of this review are to put ASOs in pharmacological context and compare their behavior as pharmacological agents to the those of siRNAs.

Protein kinase CK2 contributes to placental development: physiological and pathological implications

Preeclampsia (PE) is the most threatening pathology of human pregnancy. Its development is thought to be due to a failure in the invasion of trophoblast cells that establish the feto-maternal circulation. Protein kinase CK2 is a ubiquitous enzyme reported to be involved in the control of cell invasion. CK2 consists of two subunits, a catalytic subunit, CK2α, and a regulatory subunit, CK2β. To date, no data exist regarding the expression and role of this enzyme in normal and PE pregnancies. We performed studies, at the clinical level using distinctive cohorts from early pregnancy (n = 24) and from PE (n = 23) and age-matched controls (n = 28); in vitro, using trophoblast cell lines; ex vivo, using placental explants; and in vivo, using PE mouse models. We demonstrated that (i) CK2 is more expressed during the late first trimester of pregnancy and is mainly localized in differentiated trophoblast cells, (ii) the inhibition of its enzymatic activity decreased the proliferation, migration, invasion, and syncytialization of trophoblast cells, both in 2D and 3D culture systems, and (iii) CK2 activity and the CK2α/CK2β protein ratio were increased in PE human placentas. The pattern and profile of CK2 expression were confirmed in gravid mice along with an increase in the PE mouse models. Altogether, our results demonstrate that CK2 plays an essential role in the establishment of the feto-maternal circulation and that its deregulation is associated with PE development. The increase in CK2 activity in PE might constitute a compensatory mechanism to ensure proper pregnancy progress.

ASPsiRNA: A Resource of ASP-siRNAs Having Therapeutic Potential for Human Genetic Disorders and Algorithm for Prediction of Their Inhibitory Efficacy

Allele-specific siRNAs (ASP-siRNAs) have emerged as promising therapeutic molecules owing to their selectivity to inhibit the mutant allele or associated single-nucleotide polymorphisms (SNPs) sparing the expression of the wild-type counterpart. Thus, a dedicated bioinformatics platform encompassing updated ASP-siRNAs and an algorithm for the prediction of their inhibitory efficacy will be helpful in tackling currently intractable genetic disorders. In the present study, we have developed the ASPsiRNA resource (http://crdd.osdd.net/servers/aspsirna/) covering three components viz (i) ASPsiDb, (ii) ASPsiPred, and (iii) analysis tools like ASP-siOffTar. ASPsiDb is a manually curated database harboring 4543 (including 422 chemically modified) ASP-siRNAs targeting 78 unique genes involved in 51 different diseases. It furnishes comprehensive information from experimental studies on ASP-siRNAs along with multidimensional genetic and clinical information for numerous mutations. ASPsiPred is a two-layered algorithm to predict efficacy of ASP-siRNAs for fully complementary mutant (Eff^mut) and wild-type allele (Eff^wild) with one mismatch by ASPsiPred^SVM and ASPsiPred^matrix, respectively. In ASPsiPred^SVM, 922 unique ASP-siRNAs with experimentally validated quantitative Eff^mut were used. During 10-fold cross-validation (10nCV) employing various sequence features on the training/testing dataset (T737), the best predictive model achieved a maximum Pearson’s correlation coefficient (PCC) of 0.71. Further, the accuracy of the classifier to predict Eff^mut against novel genes was assessed by leave one target out cross-validation approach (LOTOCV). ASPsiPred^matrix was constructed from rule-based studies describing the effect of single siRNA:mRNA mismatches on the efficacy at 19 different locations of siRNA. Thus, ASPsiRNA encompasses the first database, prediction algorithm, and off-target analysis tool that is expected to accelerate research in the field of RNAi-based therapeutics for human genetic diseases.

Prediction of potent shRNAs with a sequential classification algorithm

We present SplashRNA, a sequential classifier to predict potent microRNA-based short hairpin RNAs (shRNAs). Trained on published and novel datasets, SplashRNA outperforms previous algorithms and reliably predicts the most efficient shRNAs for a given gene. Combined with an optimized miR-E backbone, >90% of high-scoring SplashRNA predictions trigger >85% protein knockdown when expressed from a single genomic integration. SplashRNA can significantly improve the accuracy of loss-of-function genetics studies and facilitates the generation of compact shRNA libraries.

Functional inhibition of chemokine receptor CCR2 by dicer-substrate-siRNA prevents pain development

BACKGROUND

Accumulating evidence suggests that the C-C chemokine ligand 2 (CCL2, or monocyte chemoattractant protein 1) acts as a neuromodulator in the central nervous system through its binding to the C-C chemokine receptor 2 (CCR2). Notably, it is well established that the CCL2/CCR2 axis plays a key role in neuron-glia communication as well as in spinal nociceptive transmission. Gene silencing through RNA interference has recently emerged as a promising avenue in research and drug development, including therapeutic management of chronic pain. In the present study, we used 27-mer Dicer-substrate small interfering RNA (DsiRNA) targeting CCR2 and assessed their ability to reverse the nociceptive behaviors induced by spinal CCL2 injection or following intraplantar injection of complete Freund's adjuvant.

RESULTS

To this end, we first developed high-potency DsiRNAs designed to target different sequences distributed across the rat CCR2 (rCCR2) messenger RNA. For optimization, methyl groups were added to the two most potent DsiRNA candidates (Evader and M7 2'-O-methyl modified duplexes) in order to improve in vivo duplex stability and to reduce potential immunostimulatory activity. Our results demonstrated that all modified candidates formulated with the cell-penetrating peptide reagent Transductin showed strong RNAi activity following intrathecal delivery, exhibiting >50% rCCR2 knockdown in lumbar dorsal root ganglia. Accordingly, we found that these DsiRNA duplexes were able to reduce spinal microglia activation and were effective at blocking CCL2-induced mechanical hypersensitivity. Along with similar reductions of rCCR2 messenger RNA, both sequences and methylation patterns were similarly effective in inhibiting the CCL2 nociceptive action for the whole seven days testing period, compared to mismatch DsiRNA. DsiRNAs against CCR2 also reversed the hypernociceptive responses observed in the complete Freund's adjuvant-induced inflammatory chronic pain model.

CONCLUSION

Altogether, these results validate CCR2 as a an appropriate molecular target for pain control and demonstrate that RNAi-based gene therapy represent an highly specific alternative to classical pharmacological approaches to treat central pathologies such as chronic pain.

In vivo siRNA distribution and pharmacokinetics assessed by nuclear imaging are modulated according to radiolabelling site

INTRODUCTION

RNA interference is efficient in in vitro studies, and appears as a therapeutic tool of major clinical interest. Nevertheless, the clinical utilisation of siRNAs is restrained by the poor availability of biodistribution data on this new class of pharmaceutics. This study aimed at defining the biodistribution and pharmacokinetics properties of an siRNA directed to the Casein Kinase-2 beta (CK2β) subunit, a potential target in cancer therapy.

METHODS

Four CK2β siRNAs were chemically modified on each extremity of sense or anti-sense strand and radioiodinated. The biodistribution of each entity was analysed in glioblastoma-bearing mice using nuclear imaging and compared to a control GFP siRNA.

RESULTS

The labelling process was associated with preservation of interference activity, except when applied to the 5' antisense terminus. Radioactivity was predominantly observed in organs of the excretory system after intravenous administration: liver, kidneys and bladder. Tumor/Contralateral muscle ratio showed significant differences depending on the labelling site. Activity associated with CK2β5's was quite constant over 2 hours, while CK2β3'as activity decreased by 40% in tumor. Finally, synchrotron X-ray analysis showed that CK2β3's is more abundant in tumor than in liver, brain or muscle, and uniformly distributed between intra- and extracellular compartments.

CONCLUSIONS

In this study, we highlighted the large influence of siRNAs radiolabelling position on their biodistribution and pharmacokinetic profiles, and proposed a systematic approach for the imaging of all siRNAs of clinical interest.

Silencing efficacy prediction: a retrospective study on target mRNA features

Post-transcriptional gene silencing is a widely used method to suppress gene expression. Unfortunately only a portion of siRNAs do successfully reduce gene expression. Target mRNA secondary structures and siRNA-mRNA thermodynamic features are believed to contribute to the silencing activity. However, there is still an open discussion as to what determines siRNA efficacy. In this retrospective study, we analysed the target accessibility comparing very high (VH) compared with low (L) efficacy siRNA sequences obtained from the siRecords Database. We determined the contribution of mRNA target local secondary structures on silencing efficacy. Both the univariable and the multivariable logistic regression evidenced no relationship between siRNA efficacy and mRNA target secondary structures. Moreover, none of the thermodynamic and sequence-base parameters taken into consideration (H-b index, ΔG°_overall, ΔG°_duplex, ΔG°_break-target and GC%) was associated with siRNA efficacy. We found that features believed to be predictive of silencing efficacy are not confirmed to be so when externally evaluated in a large heterogeneous sample. Although it was proposed that silencing efficacy could be influenced by local target accessibility we show that this could be not generalizable because of the diversity of experimental setting that may not be representative of biological systems especially in view of the many local protein factors, usually not taken into consideration, which could hamper the silencing process.

We analysed several siRNA-mRNA target features involved in silencing efficacy. We found out that features believed to be predictive of silencing efficacy are not such when transferred to a larger dataset of experiments and different experimental settings.

Size unbiased representative enzymatically generated RNAi (SURER) library and application for RNAi therapeutic screens

RNA interference (RNAi) libraries screens have become widely used for small RNA (sRNA) therapeutic targets development. However, conventional enzymatically libraries, typically prepared using the type 2 restriction enzyme MmeI, produce sRNAs between 18 and 20 bp, much shorter than the usual lengths of 19-23 bp. Here we develop a size unbiased representative enzymatically generated RNAi (SURER) library, which employs type 3 restriction modification enzyme EcoP15I to produce sRNAs ranging from 19 to 23 bp using a group of rationally designed linkers, which can completely mimic the length of sRNAs naturally generated by Dicer enzyme in living cells, and the screening results of SURER libraries showed high recombination rate and knockdown efficiency. SURER library provides a useful tool for RNAi therapeutics screening in a fast and simple way.

VIRsiRNApred: a web server for predicting inhibition efficacy of siRNAs targeting human viruses

BACKGROUND

Selection of effective viral siRNA is an indispensable step in the development of siRNA based antiviral therapeutics. Despite immense potential, a viral siRNA efficacy prediction algorithm is still not available. Moreover, performances of the existing general mammalian siRNA efficacy predictors are not satisfactory for viral siRNAs. Therefore, we have developed "VIRsiRNApred" a support vector machine (SVM) based method for predicting the efficacy of viral siRNA.

METHODS

In the present study, we have employed a new dataset of 1725 viral siRNAs with experimentally verified quantitative efficacies tested under heterogeneous experimental conditions and targeting as many as 37 important human viruses including HIV, Influenza, HCV, HBV, SARS etc. These siRNAs were divided into training (T1380) and validation (V345) datasets. Important siRNA sequence features including mono to penta nucleotide frequencies, binary pattern, thermodynamic properties and secondary structure were employed for model development.

RESULTS

During 10-fold cross validation on T1380 using hybrid approach, we achieved a maximum Pearson Correlation Coefficient (PCC) of 0.55 between predicted and actual efficacy of viral siRNAs. On V345 independent dataset, our best model achieved a maximum correlation of 0.50 while existing general siRNA prediction methods showed PCC from 0.05 to 0.18. However, using leave one out cross validation PCC was improved to 0.58 and 0.55 on training and validation datasets respectively. SVM performed better than other machine learning techniques used like ANN, KNN and REP Tree.

CONCLUSION

VIRsiRNApred is the first algorithm for predicting inhibition efficacy of viral siRNAs which is developed using experimentally verified viral siRNAs. We hope this algorithm would be useful in predicting highly potent viral siRNA to aid siRNA based antiviral therapeutics development. The web server is freely available at http://crdd.osdd.net/servers/virsirnapred/.

UP-TORR: online tool for accurate and Up-to-Date annotation of RNAi Reagents

RNA interference (RNAi) is a widely adopted tool for loss-of-function studies but RNAi results only have biological relevance if the reagents are appropriately mapped to genes. Several groups have designed and generated RNAi reagent libraries for studies in cells or in vivo for Drosophila and other species. At first glance, matching RNAi reagents to genes appears to be a simple problem, as each reagent is typically designed to target a single gene. In practice, however, the reagent-gene relationship is complex. Although the sequences of oligonucleotides used to generate most types of RNAi reagents are static, the reference genome and gene annotations are regularly updated. Thus, at the time a researcher chooses an RNAi reagent or analyzes RNAi data, the most current interpretation of the RNAi reagent-gene relationship, as well as related information regarding specificity (e.g., predicted off-target effects), can be different from the original interpretation. Here, we describe a set of strategies and an accompanying online tool, UP-TORR (for Updated Targets of RNAi Reagents; www.flyrnai.org/up-torr), useful for accurate and up-to-date annotation of cell-based and in vivo RNAi reagents. Importantly, UP-TORR automatically synchronizes with gene annotations daily, retrieving the most current information available, and for Drosophila, also synchronizes with the major reagent collections. Thus, UP-TORR allows users to choose the most appropriate RNAi reagents at the onset of a study, as well as to perform the most appropriate analyses of results of RNAi-based studies.