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PLOS Papers on Bacterial Ribosomal RNA Removal, Hantaan Virus, COVID-19 Targets

In PLOS Genetics, researchers in Korea and the US describe an enzymatic degradation-based strategy for removing ribosomal RNA from RNA sequencing data, Term-seq, and other bacterial transcriptomic or ribosome profiling experiments. The "RiboRid" protocol removes some 99.99 percent of bacterial rRNAs with the help of thermostable RNase H enzymes and targeted anti-rRNA oligonucleotide probes, the team reports, noting that the approach comes in at around $10 per sample and appears to compare favorably with conventional methods such as Ribo-Zero. Along with a RiboRid protocol, the authors prepared tools for designing custom probes and came up with a set of RiboRid probes based on sequences for almost 5,500 available bacterial sequences. "This method provides a cost-effective, rapid, and powerful alternative means to deplete rRNA that outperforms previously developed and reported methods," they write, adding that RiboRid "is valuable for routine large-scale transcriptome studies and reduces the burden of high-cost commercial kits."

A Korean University College of Medicine-led team demonstrates that the Hantaan virus (HTNV) can be detected in urine samples from infected individuals with a condition called hemorrhagic fever with renal syndrome (HFRS). As they report in PLOS Neglected Tropical Diseases, the investigators used multiplex PCR-based next-generation genome sequencing, phylogenetics, and epidemiological clues to characterize HTNV in blood serum and urine samples from four Korean patients with HFRS, detecting hantavirus sequences in samples with low levels of the virus. They note that the viral clusters and relationships between them offered clues to infection sites and sources such as Apodemus agrarius striped field mice. "Our results suggest that whole or partial genome sequences of HTNV from the urine enabled [us] to track the putative infection sites of patients with HFRS by phylogeographically linking to the zoonotic HTNV from the reservoir host captured at endemic regions," the authors write.

Potential targets for COVID-19 can be drawn from publicly available RNA sequencing data and gene signature-based drug repurposing, according to a PLOS One report by researchers at the University of Pittsburgh and the Barrow Neurological Institute. The team flagged more than 280 differentially expressed genes with a meta-analysis of published RNA-seq profiles for SARS-CoV-2-infected airway epithelial cells, including samples collected for studies of severe COVID-19, along with related drug targets and dozens of corresponding treatment candidates. The authors note that "drug targets were computationally prioritized based on gene ranking algorithms," leading to two compounds expected to target a common differentially expressed gene called CXCL10 gene. They added that the broader differentially expressed gene set "could be valuable not only as anti-COVID-19 targets but also useful for COVID-19 biomarker development."