Direct RNA nanopore sequencing of Pseudomonas aeruginosa clone C transcriptomes

Experimental and analytical pipeline for sub-genomic RNA landscape of coronavirus by Nanopore sequencer

Coronaviruses (CoVs), including severe acute respiratory syndrome coronavirus 2, can infect a variety of mammalian and avian hosts with significant medical and economic consequences. During the life cycle of CoV, a coordinated series of subgenomic RNAs, including canonical subgenomic messenger RNA and non-canonical defective viral genomes (DVGs), are generated with different biological implications. Studies that adopted the Nanopore sequencer (ONT) to investigate the landscape and dynamics of viral RNA subgenomic transcriptomes applied arbitrary bioinformatics parameters without justification or experimental validation. The current study used bovine coronavirus (BCoV), which can be performed under biosafety level 2 for library construction and experimental validation using traditional colony polymerase chain reaction and Sanger sequencing. Four different ONT protocols, including RNA direct and cDNA direct sequencing with or without exonuclease treatment, were used to generate RNA transcriptomic libraries from BCoV-infected cell lysates. Through rigorously examining the k-mer, gap size, segment size, and bin size, the optimal cutoffs for the bioinformatic pipeline were determined to remove the sequence noise while keeping the informative DVG reads. The sensitivity and specificity of identifying DVG reads using the proposed pipeline can reach 82.6% and 99.6% under the k-mer size cutoff of 15. Exonuclease treatment reduced the abundance of RNA transcripts; however, it was not necessary for future library preparation. Additional recovery of clipped BCoV nucleotide sequences with experimental validation expands the landscape of the CoV discontinuous RNA transcriptome, whose biological function requires future investigation. The results of this study provide the benchmarks for library construction and bioinformatic parameters for studying the discontinuous CoV RNA transcriptome.IMPORTANCEFunctional defective viral genomic RNA, containing all the cis-acting elements required for translation or replication, may play different roles in triggering cell innate immune signaling, interfering with the canonical subgenomic messenger RNA transcription/translation or assisting in establishing persistence infection. This study does not only provide benchmarks for library construction and bioinformatic parameters for studying the discontinuous coronavirus RNA transcriptome but also reveals the complexity of the bovine coronavirus transcriptome, whose functional assays will be critical in future studies.

Nanopore Direct RNA Sequencing Reveals the Short-Term Salt Stress Response in Maize Roots

Transcriptome analysis, relying on the cutting-edge sequencing of cDNA libraries, has become increasingly prevalent within functional genome studies. However, the dependence on cDNA in most RNA sequencing technologies restricts their ability to detect RNA base modifications. To address this limitation, the latest Oxford Nanopore Direct RNA Sequencing (ONT DRS) technology was employed to investigate the transcriptome of maize seedling roots under salt stress. This approach aimed to unveil both the RNA transcriptional profiles and alterations in base modifications. The analysis of the differential expression revealed a total of 1398 genes and 2223 transcripts that exhibited significant variation within the maize root system following brief exposure to salt stress. Enrichment analyses, such as the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway assessments, highlighted the predominant involvement of these differentially expressed genes (DEGs) in regulating ion homeostasis, nitrogen metabolism, amino acid metabolism, and the phytohormone signaling pathways. The protein-protein interaction (PPI) analysis showed the participation of various proteins related to glycolytic metabolism, nitrogen metabolism, amino acid metabolism, abscisic acid signaling, and the jasmonate signaling pathways. It was through this intricate molecular network that these proteins collaborated to safeguard root cells against salt-induced damage. Moreover, under salt stress conditions, the occurrence of variable shear events (AS) in RNA modifications diminished, the average length of poly(A) tails underwent a slight decrease, and the number of genes at the majority of the variable polyadenylation (APA) sites decreased. Additionally, the levels of N5-methylcytosine (m5C) and N6-methyladenosine (m6A) showed a reduction. These results provide insights into the mechanisms of early salt tolerance in maize.

Current concepts, advances, and challenges in deciphering the human microbiota with metatranscriptomics

Metatranscriptomics refers to the analysis of the collective microbial transcriptome of a sample. Its increased utilization for the characterization of human-associated microbial communities has enabled the discovery of many disease-state related microbial activities. Here, we review the principles of metatranscriptomics-based analysis of human-associated microbial samples. We describe strengths and weaknesses of popular sample preparation, sequencing, and bioinformatics approaches and summarize strategies for their use. We then discuss how human-associated microbial communities have recently been examined and how their characterization may change. We conclude that metatranscriptomics insights into human microbiotas under health and disease have not only expanded our knowledge on human health, but also opened avenues for rational antimicrobial drug use and disease management.

Applications of long-read sequencing to Mendelian genetics

Advances in clinical genetic testing, including the introduction of exome sequencing, have uncovered the molecular etiology for many rare and previously unsolved genetic disorders, yet more than half of individuals with a suspected genetic disorder remain unsolved after complete clinical evaluation. A precise genetic diagnosis may guide clinical treatment plans, allow families to make informed care decisions, and permit individuals to participate in N-of-1 trials; thus, there is high interest in developing new tools and techniques to increase the solve rate. Long-read sequencing (LRS) is a promising technology for both increasing the solve rate and decreasing the amount of time required to make a precise genetic diagnosis. Here, we summarize current LRS technologies, give examples of how they have been used to evaluate complex genetic variation and identify missing variants, and discuss future clinical applications of LRS. As costs continue to decrease, LRS will find additional utility in the clinical space fundamentally changing how pathological variants are discovered and eventually acting as a single-data source that can be interrogated multiple times for clinical service.

Detection of Streptococcus pyogenes M1UK in Australia and characterization of the mutation driving enhanced expression of superantigen SpeA

A new variant of Streptococcus pyogenes serotype M1 (designated 'M1_UK') has been reported in the United Kingdom, linked with seasonal scarlet fever surges, marked increase in invasive infections, and exhibiting enhanced expression of the superantigen SpeA. The progenitor S. pyogenes 'M1_global' and M1_UK clones can be differentiated by 27 SNPs and 4 indels, yet the mechanism for speA upregulation is unknown. Here we investigate the previously unappreciated expansion of M1_UK in Australia, now isolated from the majority of serious infections caused by serotype M1 S. pyogenes. M1_UK sub-lineages circulating in Australia also contain a novel toxin repertoire associated with epidemic scarlet fever causing S. pyogenes in Asia. A single SNP in the 5' transcriptional leader sequence of the transfer-messenger RNA gene ssrA drives enhanced SpeA superantigen expression as a result of ssrA terminator read-through in the M1_UK lineage. This represents a previously unappreciated mechanism of toxin expression and urges enhanced international surveillance.

baseLess: lightweight detection of sequences in raw MinION data

Summary

With its candybar form factor and low initial investment cost, the MinION brought affordable portable nucleic acid analysis within reach. However, translating the electrical signal it outputs into a sequence of bases still requires mid-tier computer hardware, which remains a caveat when aiming for deployment of many devices at once or usage in remote areas. For applications focusing on detection of a target sequence, such as infectious disease monitoring or species identification, the computational cost of analysis may be reduced by directly detecting the target sequence in the electrical signal instead. Here, we present baseLess, a computational tool that enables such target-detection-only analysis. BaseLess makes use of an array of small neural networks, each of which efficiently detects a fixed-size subsequence of the target sequence directly from the electrical signal. We show that baseLess can accurately determine the identity of reads between three closely related fish species and can classify sequences in mixtures of 20 bacterial species, on an inexpensive single-board computer.

Availability and implementation

baseLess and all code used in data preparation and validation are available on Github at https://github.com/cvdelannoy/baseLess, under an MIT license. Used validation data and scripts can be found at https://doi.org/10.4121/20261392, under an MIT license.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Bacterial tRNA landscape revisited

The updated Wobble Hypothesis reasonably explains why some 40 tRNA species are sufficient to decode the 61 amino acid codons of the Universal Genetic Code. However, we still have no clue why eubacteria lack tRNA isoacceptors with ANN anticodons, whereas eukaryotes universally lack eight GNN anticodons, only one of which is also absent in bacteria. Direct tRNA sequencing could resolve the patterns of nucleoside modification that had been driving the divergent evolution in prokaryotes and eukaryotes, but this task will require the development of AI-supported base-callers that can recognize modified nucleosides without any subsequent analytical verification. Our knowledge of the bacterial tRNA landscape is moreover broadened by the recent discovery of antisense tRNAs and tRNA-derived fragments that should be examined in their roles for gene expression, translation, bacterial physiology or metabolism.