Based on observations made following a series of genome-wide RNAi screens, a team led by University of Zurich researchers has published a report highlighting a potential flaw in published screens, and suggesting possible strategies to prevent off-target effects from confounding the results of such experiments.
The scientists conducted three siRNA screens to uncover host factors required for infection of human cells — specifically HeLa cells — by two bacterial and one viral pathogen. They discovered that most phenotypic effect of the oligos were unrelated to the intended on-target mechanism, i.e. full complementarity of the 21-nucleotide siRNA sequence to a target mRNA.
Phenotypes were actually controlled for the most part by off-target effects resulting from partial complementarity of the siRNAs to the seed region of multiple mRNAs, they wrote in the Proceedings of the National Academy of Sciences.
The team was able to predict seeds that would strongly and specifically block infection, regardless of the intended on-target effect of an siRNA — findings that were confirmed experimentally by designing oligos that lacked any on-target sequence match yet were able to reproduce the predicted phenotypes.
Indeed, seed-mediated phenotypes were found to dominate in all three screens, to an extent that "they threaten to camouflage all but the most clear-cut, strongest on-target gene effects," they wrote.
The researchers also hypothesized that published RNAi screens have unintentionally screened the sequence space of microRNA seeds rather than the intended on-target space of protein-encoding genes, which would help explain the disparity between them.
With these findings in mind, the group suggests that it should be possible to use all known human miRNA sequences, particularly their 3' UTR sections, to predict where various siRNAs might bind to mRNAs and figure out how this might lead to observed phenotypes.
"For those active seeds that happen to coincide with known, endogenous human miRNAs, it might be possible to explain some of their off-target effects by searching for predicted targets of those known miRNAs among the top hit lists of the primary screens," they added.
In an effort to improve on RNAi in phytopathogenic fungi, a group of Italian researchers has developed an alternative, plant virus vector-based gene silencing technique that does not require a plant intermediate.
Although RNAi can be induced in phytopathogenic fungi by expressing hairpin RNAs with plasmids, sequences integrated in fungal or plant genomes, or by RNAi generated in planta by a plant virus infection, these approaches all have drawbacks, the scientists wrote in PNAS. Among them are instability of hairpin constructs in fungal cells and difficulties in preparing and handling transgenic plants to silence homologous sequences in fungi grown on these plants.
As an alternative, the team demonstrated that virus-induced gene silencing can be triggered in a phytopathogenic fungus by using the direct infection of a recombinant virus vector based on the tobacco mosaic virus (TMV).
In their experiments, they showed that a wild-type isolate of TMV was able to enter fungal cells grown in a liquid medium, replicate, and persist. They also used a recombinant TMV vector carrying a gene for the ectopic expression of green fluorescent protein (GFP) to induce the stable silencing of GFP in the fungus.
In order to facilitate the therapeutic use of miRNAs, researchers from Ohio State University have constructed a web-based bioinformatics tool that enables the design of multi-targeting synthetic miRNAs.
RNAi has proven to be a promising therapeutic approach, with clinical studies showing that siRNAs can effectively silence a given target, while combinations of siRNAs can be used to hit multiple genes at once.
An alternative to this kind of siRNA cocktail are miRNAs, which are naturally intended to target multiple genes, often at multiple sites, the scientists wrote in Nucleic Acids Research.
Seeing an advantage to being able to silence multiple genes with a single construct in a therapeutic setting, the OSU scientists created miR-Synth, an online tool for designing synthetic miRNAs able to target multiple genes in multiple sites.
The tool "integrates current knowledge regarding miRNA/target interaction and features simple yet powerful options which allow, for example, [the investigation of] off-target effects and design molecules virtually not affected by [single-nucleotide polymorphisms (SNPs)] and other polymorphisms," the researchers wrote.
The system was validated through the design and testing of single- and double-target miRNAs for two prominent genes associated with lung cancer — c-MET and EGFR — with target downregulation of up to 70 percent.
MiR-Synth is available here.
Given the presence of SNPs in 3' UTRs and their ability to disrupt normal miRNA binding or introduce new binding sites, OSU researchers have developed new software for determining the effects of SNPs on miRNAs.
Although there have been multiple studies focused on predicting the location of miRNA binding sites, there are few resources available for analyzing the impact of SNPs on these sites, the researchers wrote in BMC Bioinformatics. Meanwhile, existing software for this purpose is limited by the need for significant manual labor when working with huge lists of SNPs and the fact that algorithms work only for SNPs present in databases.
The scientists therefore developed mrSNP, a web server that predicts the impact of 3' UTR SNPs on miRNA binding with a streamlined workflow and that allows users to input any SNP that has been identified by any SNP-calling program. In testing, mrSNP correctly identified 69 percent of SNPs that disrupt binding and that had been experimentally validated.
The tool can be found here.
Given the potential of miRNAs to serve as disease biomarkers, particularly given their presence in biofluids, there has been increased interest in new ways of detecting them. Current methods, however, are limited by contamination of biofluid samples, the need for special detection technologies, and the lack of established reference miRNAs to assist with normalization.
To address this, a team led by University of Oxford researchers has developed a new protocol for the detection and quantification of extracellular miRNAs in mouse serum and plasma, but which is applicable to other biofluids.
According to a report in Biological Procedures Online, the protocol covers the collection of murine serum and plasma, the extraction of biofluid RNA, miRNA quantification by RT-qPCR, and downstream data analysis.
The method was validated by quantifying miRNA abundance in wild-type and dystrophin-deficient mice, the researchers noted. Significant differences in miRNA abundance were observed depending on whether blood was taken from the jugular or tail vein, and the efficiency of miRNA recovery was reduced when sample volumes greater than 50 microliters were used.