In Vitro Inhibitory Analysis of Rationally Designed siRNAs against MERS-CoV Replication in Huh7 Cells

MERS-CoV was identified for the first time in Jeddah, Saudi Arabia in 2012 in a hospitalized patient. This virus subsequently spread to 27 countries with a total of 939 deaths and 2586 confirmed cases and now has become a serious concern globally. Camels are well known for the transmission of the virus to the human population. In this report, we have discussed the prediction, designing, and evaluation of potential siRNA targeting the ORF1ab gene for the inhibition of MERS-CoV replication. The online software, siDirect 2.0 was used to predict and design the siRNAs, their secondary structure and their target accessibility. ORF1ab gene folding was performed by RNAxs and RNAfold software. A total of twenty-one siRNAs were selected from 462 siRNAs according to their scoring and specificity. siRNAs were evaluated in vitro for their cytotoxicity and antiviral efficacy in Huh7 cell line. No significant cytotoxicity was observed for all siRNAs in Huh7 cells. The in vitro study showed the inhibition of viral replication by three siRNAs. The data generated in this study provide preliminary and encouraging information to evaluate the siRNAs separately as well as in combination against MERS-CoV replication in other cell lines. The prediction of siRNAs using online software resulted in the filtration and selection of potential siRNAs with high accuracy and strength. This computational approach resulted in three effective siRNAs that can be taken further to in vivo animal studies and can be used to develop safe and effective antiviral therapies for other prevalent disease-causing viruses.

Synthesis and evaluation of modified siRNA molecules containing a novel glucose derivative

Chemical modifications are critical for the development of safe and effective siRNAs for downstream applications.

Low Mismatch Rate between Double-Stranded RNA and Target mRNA Does Not Affect RNA Interference Efficiency in Colorado Potato Beetle

RNA interference (RNAi)-based technology has been proven as a novel approach for insect pest control. However, whether insects could evolve resistance to RNAi and the underlying mechanism is largely unknown. The target gene mutations were thought to be one of the potential ways to develop the resistance. Here we predicted the effective siRNA candidates that could be derived from dsRNA against the Colorado potato beetle (CPB) β-Actin gene (dsACT). By site-directed mutagenesis, we synthesized the dsRNAs with the defect in generation of effective siRNAs (and thus were supposed to have comparable low RNAi efficacy). We showed that, with mismatches to the target gene, all the dsRNA variants caused similar levels of silencing of target gene, mortality and larval growth retardation of CPB. Our results suggest that when the mismatch rate of dsACT and target β-Actin mRNA is less than 3%, the RNAi efficiency is not impaired in CPB, which might imply the low possibility of RNAi resistance evolving through the sequence mismatches between dsRNA and the target gene.

Targeted Inhibition of the NUP98-NSD1 Fusion Oncogene in AML

Background: NUP98-NSD1 positive AML is a poor prognostic subgroup within pediatric and adult AML (Thol et al., 2013). However, targeted therapeutics for these AML patients are not available to date. As a result of the NUP98-NSD1 fusion, NSD1 causes H3K36 hypermethylation of HOXA genes, which contributes to myeloid progenitor cell immortalization and results in AML (Wang et al., 2007). Therefore, we hypothesized that inhibition of the methyltransferase activity of NSD1 could be an effective treatment strategy for NUP98-NSD1 AML patients. Here, we assessed the efficacy of NSD1 inhibitor suramin and NUP98-NSD1-directed siRNA-containing lipid nanoparticles (LNP) in a preclinical patient-derived xenograft (PDX) model of NUP98-NSD1 leukemia. Methods: A NUP98-NSD1 positive AML patient was screened through nested PCR and Sanger sequencing. Bone marrow cells from this patient were serially transplanted into NSG (NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ) mice to establish a NUP98-NSD1 PDX model. During serial transplantations, an alternative NUP98-NSD1 fusion gene appeared. Flow-cytometry was used to check the engraftment and immunophenotype of engrafted cells. Effective siRNAs against each of the two fusion genes were developed. The microfluidic mixing technology, Nanoassemblr was used to package siRNA into LNPs and the Zetasizer was used to characterize them. Fifteen days after transplantation, suramin and solvent treatment were initiated in 9 mice per group with 10 mg/kg suramin (2 days/week for 10 weeks). For LNP treatment, treatment was initiated 3 weeks after transplantation with a once daily dose of 2.5 mg/kg on days 1-3 and then every third day thereafter for a total of 17 injections. Results: Besides the NUP98-NSD1 translocation, our patient had a FLT3-ITD mutation and a normal karyotype. In our PDX model, the engraftment of human leukemia cells reached up to 90% after ten weeks of transplantation. In successive transplantations up to the 6th generation, the NUP98-NSD1 fusion was confirmed in leukemic cells, supporting the importance of the fusion for leukemia development and stability of the model. In later transplantations, a minor clone of NUP98-NSD1 was identified. A high blast count, high WBC count, increased spleen weight, and a low hemoglobin and platelet count at death demonstrated the development of acute leukemia. High expression of myeloid markers (e.g. CD33, 99%, N=9) and negligible expression of lymphoid markers (CD3, 2%; CD19, 2%; N=9) confirmed acute myeloid leukemia. In the suramin treatment study, the mean human leukemic cell engraftment was similar between the control and treatment groups at the start of treatment (0.51%, N=9 and 0.71%, N=9, respectively), but was lower in suramin treated mice after 4 and 8 weeks of treatment (4 weeks: CTRL, 4,8%; suramin, 2,66%, P=0.1; 8 weeks: CTRL, 87,3%; suramin: 66,5%, P=0.016). No significant effect was seen on the immunophenotype of suramin and control treated leukemia cells. Suramin treatment significantly prolonged the median survival of mice compared to control mice (126 vs 114 days after transplantation, P=0.008). To establish the siRNA-LNP treatment, we identified one siRNA against each NUP98-NSD1 clone that reduced expression levels by 78% and 89.5% in the major and minor clones, respectively. The effective siRNAs were modified to increase their in vivo stability and were packaged into LNPs and used in vivo. We started the treatment when the engraftment was similar in both control LNP and NUP98-NSD1 LNP groups (0.93%, N=7 and 1.25%, N=6, respectively). After 3 weeks of treatment, LNP uptake was 99.3% and 99.2% in the CTRL LNP and NUP98-NSD1 LNP groups, respectively. The mean engraftment was lower in NUP98-NSD1 LNP mice after 5 and 8 weeks of treatment (5 weeks: CTRL LNP, 15%; NUP98-NSD1 LNP, 4.6%, P= 0.08; 8 weeks: CTRL LNP, 94.8%; NUP98-NSD1 LNP, 55.83%, P=0.007). Importantly, the NUP98-NSD1 siRNA-LNP treated mice showed a significant survival benefit compared to CTRL siRNA-LNP treated mice (106 vs 82 days after transplantation, P=0.02). Conclusions: In summary, our findings demonstrate that targeted inhibition of NUP98-NSD1 either through siRNA-LNP or suramin delays leukemia development in vivo and prolongs the survival of mice carrying a NUP98-NSD1 positive AML. Our results provide the rationale for the evaluation of NSD1 methyltransferase inhibitors and siRNA-LNP formulations in NUP98-NSD1 positive AML. Disclosures Heuser: Bayer Pharma AG, Berlin: Research Funding; Synimmune: Research Funding.

Highly efficacious antiviral protection of plants by small interfering RNAs identified in vitro

In response to a viral infection, the plant’s RNA silencing machinery processes viral RNAs into a huge number of small interfering RNAs (siRNAs). However, a very few of these siRNAs actually interfere with viral replication. A reliable approach to identify these immunologically effective siRNAs (esiRNAs) and to define the characteristics underlying their activity has not been available so far. Here, we develop a novel screening approach that enables a rapid functional identification of antiviral esiRNAs. Tests on the efficacy of such identified esiRNAs of a model virus achieved a virtual full protection of plants against a massive subsequent infection in transient applications. We find that the functionality of esiRNAs depends crucially on two properties: the binding affinity to Argonaute proteins and the ability to access the target RNA. The ability to rapidly identify functional esiRNAs could be of great benefit for all RNA silencing-based plant protection measures against viruses and other pathogens.

Genome-wide RNAi screening identifies host restriction factors critical for in vivo AAV transduction

Viral vectors based on the adeno-associated virus (AAV) hold great promise for in vivo gene transfer; several unknowns, however, still limit the vectors’ broader and more efficient application. Here, we report the results of a high-throughput, whole-genome siRNA screening aimed at identifying cellular factors regulating AAV transduction. We identified 1,483 genes affecting vector efficiency more than 4-fold and up to 50-fold, either negatively or positively. Most of these factors have not previously been associated to AAV infection. The most effective siRNAs were independent from the virus serotype or analyzed cell type and were equally evident for single-stranded and self-complementary AAV vectors. A common characteristic of the most effective siRNAs was the induction of cellular DNA damage and activation of a cell cycle checkpoint. This information can be exploited for the development of more efficient AAV-based gene delivery procedures. Administration of the most effective siRNAs identified by the screening to the liver significantly improved in vivo AAV transduction efficiency.

Prediction of siRNA Efficacy Using BP Neural Network and Support Vector Machine

RNA interference (RNAi) is a mechanism for sequence-specific, post-transcriptional down-regulation of gene expression. The success of RNAi gene silencing depends on siRNA feature design. The shortcoming of previously reported methods which design siRNA sequences based on limited rules is that they are difficult to accurately predict the efficacy that a candidate siRNA sequence will silence the target gene. With validated siRNA databases have been developed in recent years, machine learning methods can be applied to predict siRNA accuracy and optimize design. This paper proposed a combined prediction method of BP neural network and support vector machine (SVM) for selecting effective siRNA sequences. With SVM, siRNA sequences were classified into effective or ineffective siRNAs. Subsequently, BP neural network model with great learning ability selected highly effective candidate sequences from effective siRNAs. We applied this method to published siRNAs datasets, and the experimental results confirmed good prediction capability.