Aiming to address the delivery issues facing RNAi-based therapeutics development, a research team from Kobe University has developed a cancer cell-specific siRNA carrier that combines components of the hepatitis B virus and liposomes.
The investigators specifically used bio-nanocapsules, which are hollow nanoparticles composed of the L protein of HBV, the virus’ surface antigen, and a lipid bilayer, they reported in the Journal of Nanobiotechnology.
The bio-nanocapsules are highly specific for human hepatocytes and have a transfection efficiency on par with HBV, according to the paper. And, because they are viral genome-free, they have a reliable safety profile.
Previously, the Kobe University scientists altered the cell specificity of the carriers by deleting the hepatocyte-specific recognition site in the L protein and inserting binding molecules that target other cell types. In one instance, they incorporated the ZHER2 affibody molecule, which specifically recognizes epidermal growth factor receptor 2 expressed in breast and ovarian cancer cells.
“This led to successful alteration in the specificity of a BNC from hepatocytes to HER2 receptor expressing cells such as those found in breast and ovarian cancer,” they wrote.
Meanwhile, the conjugation of bio-nanocapsules and liposomes has been successfully used by other groups to encapsulate biologic materials including genes and proteins into complexes that can be tweaked by altering their phospholipid composition.
The team was able to use bio-nanocapsule/liposome complexes to specifically deliver siRNAs into HER2-expressing breast cancer cells in vitro, silencing green fluorescent protein expression by 80 percent following a 48-hour incubation period.
Though highly effective for studying gene function, RNAi screens are dependent on the availability of reagents properly mapped to target genes. As such, tools for designing RNAi reagents, while taking into account updates to the reference genome and gene annotations, are essential.
To that end, a group of researchers from Harvard Medical School have developed an online tool useful for “accurate and up-to-date annotation of cell-based in vivo RNAi reagents.”
In Genetics, the team noted that obtaining meaningful results from RNAi-based studies is “entirely reliant” on appropriately identifying the sequence-specific gene targets of the reagents being used. While target identification may seem to be a simple problem, “this is not necessarily the case.
“Even though sequences associated with RNAi reagents are static, the reference sequences and gene annotations, including gene boundaries, exon-intron boundaries and nomenclature, are constantly being updated,” they wrote. “Re-evaluations of existing RNAi libraries have shown that by the time of re-analysis, a percentage of reagents do not target any gene or are no longer predicted to be specific.”
Moreover, available tools for designing RNAi reagents do not address the “dynamic nature” of gene annotation.
In order to address this unmet need, the investigators developed the freely available online application UP-TORR, short for Updated Targets of RNAi Reagents, which automatically synchronized with gene annotations daily.
The tool includes five different query options. After selecting for species — Drosophila C. elegans, mouse, or human — users can enter the gene-specific region of an RNAi reagent sequence; enter PCR primers for dsRNA, then choose the proper PCR template; enter a list of RNAi reagent IDs; enter a list of gene identifiers for which all relevant reagents will be retrieved; enter the sequence to be targeted.
UP-TORR can be accessed here.
Next-generation sequencing has strongly impacted discoveries in microRNA biology, including the identification of novel miRNAs.
Still, miRNA discovery tools are all dependent on the availability of reference or genomic sequences. Additionally, most require the identification of miRNA precursors, limiting advances in the field.
“This has resulted into a sort of knowledge skew where most of the miRNAs have been reported only for those species whose genomic sequences are available or homologous sequences are known,” researchers from Vanderbilt University wrote in PLoS One.
To overcome this hurdle, the investigators reported a novel approach to discovering miRNAs without the need for genomic/reference sequences. Called miReader, it uses next-generation sequencing read data to build miRNA models through a multi-boosting algorithm with best-first tree as its base classifier.
The team tested the resource over large amounts of experimental data from human, plants, nematode, zebrafish, and fruitfly, and found it performed with more than 90 percent accuracy. Using the tool over Illumina read data for Miscanthus, a plant whose genome has not been sequenced, the team found 21 novel mature miRNA duplex candidates.
“This has clearly demonstrated that in spite of unavailability of genomic sequences … miReader could accurately identify the mature miRNAs directly from small RNA sequencing data,” the team concluded.
Despite the existence of Northern blot, PCR, and other tools for analyzing miRNA expression, there is currently no available means for consecutive functional monitoring of their expression in real time.
Therefore, a research team from the National Institute for Viral Disease Control and Prevention in China has developed Asensor, a recombinant adeno-associated viral vector-based miRNA sensor for miRNA monitoring in live cells.
The tool was constructed by inserting a given miRNA target sequence into the 3’-UTR of reporter genes and containing two independent expression cassettes encoding Gaussia luciferase and firefly luciferase, according to a paper in PLoS One. With Asensor, miRNA activity is inferred by measuring the inhibition of reporter gene expression.
To test the approach, the team monitored the real-time activity of miR-200a, -200b, -21, -96, -146a, -10a, -155, and -221 in four cell lines derived from pancreatic cancer, as well as a no-cancer cell line as a normal pancreas control.
“Although the miRNA profiles were diverse, based on our data, these five cell lines could be divided into three groups,” they wrote in their paper.
The adenocarcinoma cells were similar in eight miRNA profiles, all miRNAs negatively regulated expression of the target mRNA, and they shared a similar tendency of miRNA activity. Meanwhile, the epithelioid carcinoma cell line was “significantly different from the other four cell lines, with many of the miRNAs displaying upregulation of the target mRNA expression, which deviates from the current opinion on miRNA function.”
While sandwich hybridization is often used in RNA- and DNA-detection assays to improve probe-target recognition over background noise, the approach cannot be employed for short nucleic acid targets such as miRNAs because probe binding is typically too weak.
As a result, miRNA detection is usually conducted using enzymatic methods such as polyadenylation and hybridization-mediated ligation, which can be time-consuming and expensive.
To address this problem, researchers from Carnegie Mellon University have developed a method for the rapid and stable sandwich hybridization detection of short nucleic acid targets. The approach involves the use of an n-alkylatyed, polyethylene glycol gamma-carbon modified peptide nucleic acid amphiphile, or an gamma-PNA, they reported in Biomacromolecules.
The gamma-PNA’s “exceptionally high affinity” permits stable hybridization of a second DNA-based probe to the remaining bases of the short target, the researchers wrote. “Upon hybridization of both probes, an electrophoretic mobility shift is measured via interaction of the n-alkane modification on the [gamma-PNA] with capillary electrophoresis running buffer containing nonionic surfactant micelles.”
The sandwich hybridization of both probes is stable under different binding configurations and is further stabilized by coaxial stacking upon hybridization of the adjacent probe. The assay is also capable of distinguishing single-base mismatches at many locations along the target by increasing the capillary temperature, they added.
The group used the method to detect short, 22-nucleotide DNA and RNA targets, and state that it should be “straightforward” to adapt the technique for high-throughput profiling of miRNA expression levels.