NERD-seq: a novel approach of Nanopore direct RNA sequencing that expands representation of non-coding RNAs.

Non-coding RNAs (ncRNAs) are frequently documented RNA modification substrates. Nanopore Technologies enables the direct sequencing of RNAs and the detection of modified nucleobases. Ordinarily, direct RNA sequencing uses polyadenylation selection, studying primarily mRNA gene expression. Here, we present NERD-seq, which enables detection of multiple non-coding RNAs, excluded by the standard approach, alongside natively polyadenylated transcripts. Using neural tissues as a proof of principle, we show that NERD-seq expands representation of frequently modified non-coding RNAs, such as snoRNAs, snRNAs, scRNAs, srpRNAs, tRNAs, and rRFs. NERD-seq represents an RNA-seq approach to simultaneously study mRNA and ncRNA epitranscriptomes in brain tissues and beyond.

Quantum analysis of squiggle data.

Squiggle data is the numerical output of DNA and RNA sequencing by the Nanopore next generation sequencing platform. Nanopore sequencing offers expanded applications compared to previous sequencing techniques but produces a large amount of data in the form of current measurements over time. The analysis of these segments of current measurements require more complex and computationally intensive algorithms than previous sequencing technologies. The purpose of this study is to investigate in principle the potential of using quantum computers to speed up Nanopore data analysis. Quantum circuits are designed to extract major features of squiggle current measurements. The circuits are analyzed theoretically in terms of size and performance. Practical experiments on IBM QX show the limitations of the state of the art quantum computer to tackle real life squiggle data problems. Nevertheless, pre-processing of the squiggle data using the inverse wavelet transform, as experimented and analyzed in this paper as well, reduces the dimensionality of the problem in order to fit a reasonable size quantum computer in the hopefully near future.

Genomic Characterization of Carbapenem-Resistant Bacteria from Beef Cattle Feedlots.

Carbapenems are considered a last resort for the treatment of multi-drug-resistant bacterial infections in humans. In this study, we investigated the occurrence of carbapenem-resistant bacteria in feedlots in Alberta, Canada. The presumptive carbapenem-resistant isolates (n = 116) recovered after ertapenem enrichment were subjected to antimicrobial susceptibility testing against 12 different antibiotics, including four carbapenems. Of these, 72% of the isolates (n = 84) showed resistance to ertapenem, while 27% of the isolates (n = 31) were resistant to at least one other carbapenem, with all except one isolate being resistant to at least two other drug classes. Of these 31 isolates, 90% were carbapenemase positive, while a subset of 36 ertapenem-only resistant isolates were carbapenemase negative. The positive isolates belonged to three genera; Pseudomonas, Acinetobacter, and Stenotrophomonas, with the majority being Pseudomonas aeruginosa (n = 20) as identified by 16S rRNA gene sequencing. Whole genome sequencing identified intrinsic carbapenem resistance genes, including blaOXA-50 and its variants (P. aeruginosa), blaOXA-265 (A. haemolyticus), blaOXA-648 (A. lwoffii), blaOXA-278 (A. junii), and blaL1 and blaL2 (S. maltophilia). The acquired carbapenem resistance gene (blaPST-2) was identified in P. saudiphocaensis and P. stutzeri. In a comparative genomic analysis, clinical P. aeruginosa clustered separately from those recovered from bovine feces. In conclusion, despite the use of selective enrichment methods, finding carbapenem-resistant bacteria within a feedlot environment was a rarity.

Interactive microbial genome visualization with GView.

SUMMARY: GView is a Java application for viewing and examining prokaryotic genomes in a circular or linear context. It accepts standard sequence file formats and an optional style specification file to generate customizable, publication quality genome maps in bitmap and scalable vector graphics formats. GView features an interactive pan-and-zoom interface, a command-line interface for incorporation in genome analysis pipelines, and a public Application Programming Interface for incorporation in other Java applications. AVAILABILITY: GView is a freely available application licensed under the GNU Public License. The application, source code, documentation, file specifications, tutorials and image galleries are available at http://gview.ca.