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Background Direct RNA sequencing (dRNA-seq) on the Oxford Nanopore Technologies (ONT) platforms can produce reads covering up to full-length gene transcripts, while containing decipherable information about RNA base modifications and poly-A tail lengths. Although many published studies have been expanding the potential of dRNA-seq, its sequencing accuracy and error patterns remain understudied. Results We present the first comprehensive evaluation of sequencing accuracy and characterisation of systematic errors in dRNA-seq data from diverse organisms and synthetic in vitro transcribed RNAs. We found that for sequencing kits SQK-RNA001 and SQK-RNA002, the median read accuracy ranged from 87% to 92% across species, and deletions significantly outnumbered mismatches and insertions. Due to their high abundance in the transcriptome, heteropolymers and short homopolymers were the major contributors to the overall sequencing errors. We also observed systematic biases across all species at the levels of single nucleotides and motifs. In general, cytosine/uracil-rich regions were more likely to be erroneous than guanines and adenines. By examining raw signal data, we identified the underlying signal-level features potentially associated with the error patterns and their dependency on sequence contexts. While read quality scores can be used to approximate error rates at base and read levels, failure to detect DNA adapters may be a source of errors and data loss. By comparing distinct basecallers, we reason that some sequencing errors are attributable to signal insufficiency rather than algorithmic (basecalling) artefacts. Lastly, we generated dRNA-seq data using the latest SQK-RNA004 sequencing kit released at the end of 2023 and found that although the overall read accuracy increased, the systematic errors remain largely identical compared to the previous kits. Conclusions As the first systematic investigation of dRNA-seq errors, this study offers a comprehensive overview of reproducible error patterns across diverse datasets, identifies potential signal-level insufficiency, and lays the foundation for error correction methods.

Programmed ribosomal frameshifting (PRF) is a fundamental gene expression event in many viruses, including SARS-CoV-2. It allows production of essential viral, structural and replicative enzymes that are encoded in an alternative reading frame. Despite the importance of PRF for the viral life cycle, it is still largely unknown how and to what extent cellular factors alter mechanical properties of frameshift elements and thereby impact virulence. This prompted us to comprehensively dissect the interplay between the SARS-CoV-2 frameshift element and the host proteome. We reveal that the short isoform of the zinc-finger antiviral protein (ZAP-S) is a direct regulator of PRF in SARS-CoV-2 infected cells. ZAP-S overexpression strongly impairs frameshifting and inhibits viral replication. Using in vitro ensemble and single-molecule techniques, we further demonstrate that ZAP-S directly interacts with the SARS-CoV-2 RNA and interferes with the folding of the frameshift RNA element. Together, these data identify ZAP-S as a host-encoded inhibitor of SARS-CoV-2 frameshifting and expand our understanding of RNA-based gene regulation. Programmed ribosomal frameshifting (PRF) occurs in many viruses including SARS-CoV-2 to allow the translation of multiple proteins from a single transcript. Here, the authors identify the human short isoform of the zinc-finger antiviral protein (ZAP-S) as a direct regulator of PRF in SARS-CoV-2 that severely impairs SARS-CoV-2 frameshifting in cells and directly interacts with the SARS-CoV-2 RNA; interfering with the folding of the frameshift RNA element.

Genome-wide measurements of RNA structure can be obtained using reagents that react with unpaired bases, leading to adducts that can be identified by mutational profiling on next-generation sequencing machines. One drawback of these experiments is that short sequencing reads can rarely be mapped to specific transcript isoforms. Consequently, information is acquired as a population average in regions that are shared between transcripts, thus blurring the underlying structural landscape. Here, we present nanopore dimethylsulfate mutational profiling (Nano-DMS-MaP)—a method that exploits long-read sequencing to provide isoform-resolved structural information of highly similar RNA molecules. We demonstrate the value of Nano-DMS-MaP by resolving the complex structural landscape of human immunodeficiency virus-1 transcripts in infected cells. We show that unspliced and spliced transcripts have distinct structures at the packaging site within the common 5′ untranslated region, likely explaining why spliced viral RNAs are excluded from viral particles. Thus, Nano-DMS-MaP is a straightforward method to resolve biologically important transcript-specific RNA structures that were previously hidden in short-read ensemble analyses. Nano-DMS-MaP combines the power of DMS mutational profiling and long-read nanopore sequencing to resolve structural differences among RNA isoforms, revealing the structural landscape of HIV-1 transcripts in cells.

Nanopore direct RNA sequencing (dRNA-seq) enables unique insights into RNA biology. However, applications are currently limited by the lack of accurate and cost-effective sample multiplexing. Here we introduce WarpDemuX, an ultra-fast and highly accurate adapter-barcoding and demultiplexing approach for dRNA-seq with SQK-RNA002 and SQK-RNA004 chemistries. WarpDemuX enhances speed and accuracy by fast processing of the raw nanopore signal, use of a light-weight machine-learning algorithm and design of optimized barcode sets. We demonstrate its utility by performing rapid phenotypic profiling of different SARS-CoV-2 viruses through multiplexed sequencing of longitudinal samples on a single flowcell, identifying systematic differences in transcript abundance and poly(A) tail lengths during infection. Additionally, integrating WarpDemuX into sequencing control software enables real-time enrichment of target molecules through barcode-specific adaptive sampling, which we demonstrate by enriching low abundance viral RNA. In summary, WarpDemuX represents a broadly applicable, high-performance, economical multiplexing solution for dRNA-seq, facilitating advanced (epi-) transcriptomic research. Applications of nanopore direct RNA sequencing (dRNA) are limited by the lack of accurate and cost-effective sample multiplexing. Here, the authors report an ultra-fast and high accurate adapter-barcoding and demultiplexing approach for dRNA and demonstrate its application in SARS-CoV-2 viruses.

RNA structure determination is essential to understand how RNA carries out its diverse biological functions. In cells, RNA isoforms are readily expressed with partial variations within their sequences due, for example, to alternative splicing, heterogeneity in the transcription start site, RNA processing or differential termination/polyadenylation. Nanopore dimethyl sulfate mutational profiling (Nano-DMS-MaP) is a method for in situ isoform-specific RNA structure determination. Unlike similar methods that rely on short sequencing reads, Nano-DMS-MaP employs nanopore sequencing to resolve the structures of long and highly similar RNA molecules to reveal their previously hidden structural differences. This Protocol describes the development and applications of Nano-DMS-MaP and outlines the main considerations for designing and implementing a successful experiment: from bench to data analysis. In cell probing experiments can be carried out by an experienced molecular biologist in 3–4 d. Data analysis requires good knowledge of command line tools and Python scripts and requires a further 3–5 d. Key points Nano-DMS-MaP is a method for in situ isoform-specific RNA structure determination. It employs nanopore sequencing to resolve the structures of long and highly similar RNA molecules, revealing previously hidden structural differences. Compared with short-read sequencing, in which it is difficult to uniquely map individual reads to highly similar transcript isoforms, Nano-DMS-MaP uses long-read Nanopore sequencing, enabling unambiguous assignment of reads to transcript isoforms. A protocol for Nano-DMS-MaP, a method for in situ isoform-specific RNA structure determination. The technique employs nanopore sequencing to resolve the structures of long and highly similar RNA molecules, revealing previously hidden structural differences.

Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, 'brain-predicted age', derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N=2001), then tested in the Lothian Birth Cohort 1936 (N=669), to determine relationships with age-associated functional measures and mortality. Having a brain-predicted age indicative of an older-appearing brain was associated with: weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk. Furthermore, while combining brain-predicted age with grey matter and cerebrospinal fluid volumes (themselves strong predictors) not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death.

Bacterial noncoding RNAs fulfill a variety of cellular functions as catalysts, as scaffolds in protein complexes or as regulators of gene expression. They often exhibit complex tertiary structures that are a key determinant of their biochemical function. Here, we characterize the structured “ raiA motif” RNA from Clostridioides difficile , which is conserved in more than 2,500 bacterial species from the phyla Bacillota and Actinomycetota. We show that its transcript abundance and stability in exponentially growing bacteria rivals that of ribosomal RNAs. Deletion of the “ raiA motif” RNA is associated with delayed transition into stationary phase, and changes in stationary phase pathways such as spore formation, hence we rename it ModT ( mod ulator of t ransition phase). Mechanistically, we show that ModT-mediated changes in cellular cyclic di-GMP levels are linked to the pronounced sporulation defect in the modT mutant. Importantly, we show that expression profiles and isoform patterns of ModT are conserved in Clostridium perfringens and Paeniclostridium sordellii , and that these orthologs can functionally complement ModT in C . difficile . Chemical structure probing of ModT in vivo reveals dynamic refolding and provides initial evidence for a potential association of ModT with proteins. In summary, our findings indicate that ModT fulfills a conserved role in regulating growth transitions in bacteria and provide a crucial step towards delineating its molecular mechanism.

Influenza A viruses cause annual influenza epidemics and occasional severe pandemics. Their genome is segmented into eight fragments, which offers evolutionary advantages but complicates genomic packaging. The existence of a selective packaging mechanism, in which one copy of each viral RNA is specifically packaged into each virion, is suspected, but its molecular details remain unknown. Here, we identified a direct intermolecular interaction between two viral genomic RNA segments of an avian influenza A virus using in vitro experiments. Using silent trans -complementary mutants, we then demonstrated that this interaction takes place in infected cells and is required for optimal viral replication. Disruption of this interaction did not affect the HA titer of the mutant viruses, suggesting that the same amount of viral particles was produced. However, it nonspecifically decreased the amount of viral RNA in the viral particles, resulting in an eightfold increase in empty viral particles. Competition experiments indicated that this interaction favored copackaging of the interacting viral RNA segments. The interaction we identified involves regions not previously designated as packaging signals and is not widely conserved among influenza A virus. Combined with previous studies, our experiments indicate that viral RNA segments can promote the selective packaging of the influenza A virus genome by forming a sequence-dependent supramolecular network of interactions. The lack of conservation of these interactions might limit genetic reassortment between divergent influenza A viruses.

RNA dimerization is the noncovalent association of two human immunodeficiency virus-1 (HIV-1) genomes. It is a conserved step in the HIV-1 life cycle and assumed to be a prerequisite for binding to the viral structural protein Pr55 Gag during genome packaging. Here, we developed functional analysis of RNA structure-sequencing (FARS-seq) to comprehensively identify sequences and structures within the HIV-1 5′ untranslated region (UTR) that regulate this critical step. Using FARS-seq, we found nucleotides important for dimerization throughout the HIV-1 5′ UTR and identified distinct structural conformations in monomeric and dimeric RNA. In the dimeric RNA, key functional domains, such as stem-loop 1 (SL1), polyadenylation signal (polyA) and primer binding site (PBS), folded into independent structural motifs. In the monomeric RNA, SL1 was reconfigured into long- and short-range base pairings with polyA and PBS, respectively. We show that these interactions disrupt genome packaging, and additionally show that the PBS–SL1 interaction unexpectedly couples the PBS with dimerization and Pr55 Gag binding. Altogether, our data provide insights into late stages of HIV-1 life cycle and a mechanistic explanation for the link between RNA dimerization and packaging. Comprehensive functional and structural probing of the HIV-1 5′ untranslated region reveals novel interactions that regulate RNA dimerization, Pr55Gag binding and genome packaging into virions.

Targeting of diseased cells is one of the most urgently needed prerequisites for a next generation of potent pharmaceuticals. Different approaches pursued fail mainly due to a lack of specific surface markers. Developing an RNA-based methodology, we can now ensure precise cell targeting combined with selective expression of effector proteins for therapy, diagnostics or cell steering. The specific combination of the molecular properties of antisense technology and mRNA therapy with functional RNA secondary structures allowed us to develop selectively expressed RNA molecules for medical applications. These seRNAs remain inactive in non-target cells and induce translation by partial degradation only in preselected cell types of interest. Cell specificity and type of functionalization are easily adaptable based on a modular system. In proof-of-concept studies we use seRNAs as platform technology for highly selective cell targeting. We effectively treat breast tumor cell clusters in mixed cell systems and shrink early U87 glioblastoma cell clusters in the brain of male mice without detectable side effects. Our data open up potential avenues for various therapeutic applications. Targeting of diseased cells is key to the development of next-generation pharmaceuticals, but is often hindered by a lack of specific cell surface markers. Here the authors develop an RNA-based approach, which allows precise control of gene expression, with translation only occurring within preselected cell types of interest.