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Tools & Techniques: Multi-Targeting RNA Duplex; RNAi System for Fungi; and More

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Seeing therapeutic potential for RNAi molecules capable of silencing multiple targets, a team of Korean researchers from industry and academia has developed a novel, cross-shaped RNA duplex that can target four cellular genes simultaneously.

The team previously developed tripodal RNAi-triggering molecules that knocked down three targets while exhibiting enhanced intracellular delivery versus conventional siRNAs when complexed with Polyplus Transfections’ jetPEI, a linear polyethyleneimine, they wrote in Molecules and Cells.

Building on this work, they created qiRNAs by annealing four chemically synthesized 38-nucleotide single-stranded RNAs, and designed them against four cancer-associated targets: survivin, beta-catenin, STAT3, and c-MET.

“The qiRNA structure was designed so that the 5’-end of the antisense strand of each siRNA unit was orientated towards the outside, as our previous studies showed that this arrangement maintains the gene silencing activity of the individual siRNA units in longer RNA duplexes,” the investigators wrote.

The found that the siRNAs were able to silence all their targets in HeLa cells when transfected with polyethyleneimine, and used 5’ RACE analysis to confirm an RNAi effect. Further testing showed that the antisense strands of the molecule can be stably incorporated into Argonaute2 in its full-length form to trigger RNAi silencing.

Notably, qiRNAs proved more effective when delivered with polyethyleneimine than standard siRNAs, suggesting “the presence of a unique mode of interaction between branched small RNA molecules and jetPEI to form a stronger complex,” according to the paper.

Overall, qiRNAs expand the “structural diversity repertoire” of RNAi molecules and offer evidence of the flexibility of human RISC in guiding RNAi interactions, the researchers concluded. Meantime, the ability of qiRNAs to hit multiple targets offers the potential for their use in novel RNAi therapeutics.


Given the importance of fungi in biodegradation, as well as in the industrial production of biochemical, there is a need for tools for their genetic manipulation. While homologous recombination has been used, it has low efficiency in many types of fungi.

To address this, a group of Chinese researchers has developed an efficient RNAi system for fungi, focusing on the filamentous fungus Trichoderma koningii, which is widely used to control plant diseases caused by other fungi, according to a paper in Folia Microbiologica.

Using DsRed as a reporter, the scientists created a recombinant strain of T. koningii that stably expresses the fluorescent protein, they wrote. A vector-directing expression of a DsRed hairpin RNA was then constructed and transformed into the T. koningii recipient strain.

About 79 percent of the transformed T. koningii displayed decreased DsRed fluorescence, with complete suppression in some of the fungus.

“Characterization of randomly selected transformants by genomic DNA PCR analysis, real-time PCR quantification, and western blot confirmed downregulation of gene expression at different levels,” the team noted.

Having demonstrated RNAi in the fungus, the investigators wrote that their approach “promises to accelerate our understanding of fungal processes, permitting increasingly rapid targeted genetic manipulation and the continued optimization of current and future industrially utilized fungi.”


As RNAi becomes a standard technique for target gene perturbation, computational approaches for reverse engineering parts of biological networks from measure-able effects of genetic perturbations have become increasingly popular. Yet these are primarily based on gene-expression data, with little focus on phenotypic data.

A multi-institute team of German researchers has recently published in Bioinformatics a method for inferring gene networks from high-dimensional phenotypic perturbation effects on single cells recorded using time-lapse microscopy.

“At the heart of the method lies the extraction of morphological features yielding measurable differences in cell phenotypes,” the researchers wrote in their paper. To quantify these differences, “cell trajectories were automatically aligned to the standard cell cycle, and a likelihood ratio score for the detection of feature changes was calculated.”

Dynamic nested effects models were used to estimate parts of the network structure between perturbed genes via a novel Markov chain Monte Carlo approach.

In simulation experiments, the method demonstrated high sensitivity and specificity, which is reflected in its application to movies of 22 siRNA knockdowns from the Mitocheck database, where all estimated interactions were explainable by literature-known pathways, according to the paper.

Targeted RNAi screens have shown great potential in the reconstruction of cellular networks, and given that -omics data is not always available, image-based techniques can offer “a promising alternative,” the team concluded.


Aiming to address the delivery hurdle that can limit the in vivo use of siRNAs, a group of researchers from Hokkaido University has developed a carrier based on a novel pH-sensitive cationic lipid called YSK05 for the RNAi molecules.

According to a paper appearing in Molecular Therapy, the delivery vehicle — dubbed MEND, for multifunctional envelope-type nanodevice — was able to deliver siRNAs into tumor tissue in vivo after systemic administration. Pegylation of the carrier boosted siRNA accumulation in tumors from 0.0079 percent ID/g to 1.9 percent ID/g.

Meanwhile, MEND-delivered siRNAs were able to achieve a roughly 50 percent reduction in target gene expression at 3 mg/kg, which the scientists said is sufficient for “experimental use,” with no observed toxicities.

“An appropriately prepared MEND can be a novel tool for the investigations of the in vivo molecular biology of cancer and remains a viable basic technology for serving as an siRNA medicine in the future,” they concluded.

The Scan

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