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Moss, W.

Publications and source records attributed to Moss, W..

8 recordsLinked to original sources

ScanFold3: a robust and rapid approach for identifying structured RNA targets in genomes and transcriptomes

Background. The rapid expansion of high-throughput transcriptomic datasets has created a critical need for scalable tools to identify functional RNA secondary structures. While thermodynamics-based folding is a well-established method, most algorithms lack the scalability required for genomic-scale datasets due to O(n3) time complexity. Methods. We present ScanFold3, an enhanced version of the ScanFold pipeline that optimizes the "Fold" step for modern computing needs. This version models consensus structure generation as a minimum perfect weighted matching problem on a graph. To ensure maximum scalability, we implemented a Greedy Approximation Algorithm and optimized performance-critical components in C++. Results. Benchmarking on sequences up to 128 kb demonstrates that ScanFold3 achieves a 38-fold to 129-fold increase in speed over ScanFold2. Validation against annotated human RNAs shows that ScanFold3 offers improved positive predictive value (PPV). Most significantly, when ScanFold3 outputs are used as structural constraints for global refolding, it outperforms previous versions across all metrics, including the F1 score. Conclusions. ScanFold3 provides a robust, speedy, and user-friendly method for characterizing the thermodynamics of novel RNA and DNA sequences. It is designed as an efficient first step for high throughput bioinformatic pipelines, capable of paring down chromosome-scale transcriptomic data into stable structures amenable to advanced analysis.

bioinformatics↗

Live-Cell Covalent Profiling Reveals Principles of RNA-Small Molecule Recognition across the Human Transcriptome

RNA folds are abundant in mammalian cells yet poorly characterized as small-molecule targets. We present a scalable, unbiased live-cell pipeline that maps where small molecules bind RNA across the human transcriptome and convert those binders into selective degraders. A 200-member fragment library bearing diazirine/alkyne handles yielded 23 RNA-binding candidates. Chem-CLIP-Map-Seq in MDA-MB-231 cells identified 723 RNA targets and their binding sites, revealing a strong bias toward 5' and 3' untranslated regions (UTRs) in mRNAs and enrichment at thermodynamically stable structures, with limited binding to non-coding RNAs. Expression level and local stability contributed to engagement. An integrated machine-learning model trained on multiple fingerprints distinguished binders from non-binders, and highlighted chemotypes and physicochemical features that favor RNA recognition. Four fragments were converted to RiboTACs; despite broad binding, cleavage was highly selective, with X1-RiboTAC degrading MPP7 and SSC4D mRNAs in an RNase L-dependent manner and reducing their protein levels. A competitive profiling workflow quantified in-cell target occupancy and guided optimization of the RNA-binding module to reprogram selectivity: an X1 derivative produced an MPP7-selective RiboTAC that lowered MPP7 mRNA levels and suppressed breast-cancer cell migration, while sparing SSC4D transcripts. This end-to-end framework, including transcriptome-wide mapping, data-driven rules, and tunable degradation, establishes practical principles for ligandable RNA sites in cells and enables rational design of RNA-targeted small molecules and degraders. TEASERLive-cell mapping reveals ligandable RNA sites and guides design of selective RNA degraders. TOC graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=61 SRC="FIGDIR/small/686775v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@a216c8org.highwire.dtl.DTLVardef@185c59eorg.highwire.dtl.DTLVardef@17131e2org.highwire.dtl.DTLVardef@81ffa2_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

Identification of a conserved RNA structure in the TNFRSF1A 3'UTR: Implications for post-transcriptional regulation

Tumor necrosis factor receptor superfamily 1A gene (TNFRSF1A) encodes the TNFR1 protein, a critical regulator of inflammation implicated in various diseases. Using ScanFold with the Integrative Genomics Viewer (IGV) GUI, we identified novel RNA structural elements within the TNFRSF1A gene. Focusing on the 3UTR, these structures were characterized using reporter assays and targeted DMS-MaPseq. We identified a structured region that may play a role in regulating TNFR1 translation and that was also found to associate with HuR, a key regulatory RNA-binding protein. These findings provide a framework for identifying and characterizing potential functional RNA structures in therapeutically relevant genes, suggesting a new layer of post-transcriptional regulation for TNFR1 expression.

molecular biology↗

ANALYSIS OF RESPIRATORY SYNCYTIAL VIRUS REVEALS CONSERVED RNA SECONDARY STRUCTURAL MOTIFS AND IMPACT VIRAL LIFECYCLE

An analysis that combined bioinformatics, comparative sequence/structural analysis, and experimental assays has been completed on respiratory syncytial virus (RSV). Both the genomic RNA and its reverse complement were studied using the novel bioinformatics pipeline ScanFold, which predicted 49 regions on RSV RNAs that appear to encode functional secondary structures (based on their unusually stable sequence order). Multiple motifs appear to be conserved between RSV and related virus strains, including one region within the F gene, which had a highly favorable overall prediction metric of a paired secondary structure. This motif was subjected to additional experimental analyses using SHAPE analysis to confirm ScanFold predicted secondary structure. In subsequent analysis, RSV F mRNA transcripts were made by in vitro transcription using T7 polymerase and transcripts which relaxed the predicted secondary structure yielded slightly higher mRNA transcripts and protein expression levels as wildtype F. However, using reverse genetics for comparison of viruses containing wildtype or relaxed F suggested that the predicted secondary structures may be critical for RSV replication in cells. To our knowledge, this is the first study to examine conserved RNA structures across multiple RSV strains and may help identify potential therapeutic targets to inhibit.

microbiology↗

Sequences at gene segment termini inclusive of untranslated regions and partial open reading frames play a critical role in mammalianorthoreovirus S gene packaging

Mammalian orthoreovirus (MRV) is a prototypic member of the Spinareoviridae family and has ten double-stranded RNA segments. One copy of each segment must be faithfully packaged into the mature virion, and prior literature suggests that nucleotides (nts) at the terminal ends of each gene likely facilitate their packaging. However, little is known about the precise packaging sequences required or how the packaging process is coordinated. Using a novel approach, we have determined that 200 nts at each terminus, inclusive of untranslated regions (UTR) and parts of the open reading frame (ORF), are sufficient for packaging each S gene segment (S1-S4) individually and together into replicating virus. Further, we mapped the minimal sequences required for packaging the S1 gene segment to 25 5' nts and 50 3' nts. The S1 UTRs alone are not sufficient, but are necessary for packaging, as mutations of the 5' or 3' UTRs led to a complete loss of virus recovery. Using a second novel assay, we determined that 50 5'nts and 50 3' nts of S1 are sufficient to package a non-viral gene segment into MRV. The 5' and 3' termini of the S1 gene are predicted to form a panhandle structure and specific mutations within the predicted stem of the panhandle region led to a significant decrease in viral recovery. Additionally, mutation of six nts that are conserved in the three major serotypes of MRV and are predicted to form an unpaired loop in the S1 3'UTR, led to a complete loss of viral recovery. Overall, our data provide strong experimental proof that MRV packaging signals lie at the terminal ends of the S gene segments and offer support that the sequence requirements for efficient packaging of the S1 segment include a predicted panhandle structure and specific sequences within an unpaired loop in the 3' UTR.

microbiology↗

Analysis of RNA sequence and structure in key genes of Mycobacterium ulcerans reveals conserved structural motifs and regions with apparent pressure to remain unstructured

Buruli Ulcer is a neglected tropical disease that results in disfiguring and potentially dangerous lesions in affected persons across a wide geographic area, which includes much of West Africa. The causative agent of Buruli Ulcer is Mycobacterium ulcerans, a relative of the bacterium that causes tuberculosis and leprosy. Few therapeutic options exist for the treatment of this disease beyond the main approach, surgical removal, which is frequently ineffective. In this study we analyze six genes in Mycobacterium ulcerans that have high potential of therapeutic targeting. We focus our analysis on a combined in silico and comparative sequence study of potential RNA secondary structure across these genes. The end result of this work was the comprehensive local RNA structural landscape across each of these significant genes. This revealed multiple sites of ordered and evolved RNA structure interspersed between sequences that either have no bias for structure or, indeed, appear to be ordered to be unstructured and (potentially) accessible. In addition to providing data that could be of interest to basic biology, our results provide guides for efforts aimed at targeting this pathogen at the RNA level. We explore this latter possibility through the in silico analysis of antisense oligonucleotides that could be used to target pathogen RNA. Author SummaryBuruli Ulcer is a neglected tropical necrotizing skin disease endemic to West Africa and several other developing countries. The disease is known to be caused by Mycobacterium ulcerans, but the mode of transmission is not well understood. Here, we present findings on the RNA secondary structural landscape of key genes found in its genome and virulence plasmid. We also suggest potential therapeutic strategies to treat this disease that leverage a better understanding of RNA secondary structure. In our analysis we have predicted regions within these genes that are potentially ordered by evolution to have unusual structural stability and likely functionality, as well as regions that lack stable structure and may be unordered for accessibility. These structured regions can act as potential targets of both antisense oligonucleotide and small molecule therapeutics, while the unstructured regions may be most advantageous for only antisense oligonucleotides. Both strategies have been proven to be effective in other bacterial and viral pathogens; therefore, adaptation to this neglected disease may prove beneficial to developing more effective and efficient treatment options. Through our analysis of the RNA secondary structure landscape of key genes in M. ulcerans, we hope to provide other researchers with new avenues for development of novel therapeutic strategies to treat this devastating and neglected disease.

bioinformatics↗

SARS-CoV-2 expresses a microRNA-like small RNA able to selectively repress host genes

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease (COVID-19), continues to be a pressing health concern. In this study, we investigated the impact of SARS-CoV-2 infection on host microRNA (miRNA) populations in three human lung-derived cell lines, as well as in nasopharyngeal swabs from SARS-CoV-2 infected individuals. We did not detect any major and consistent differences in host miRNA levels after SARS-CoV-2 infection. However, we unexpectedly discovered a viral miRNA-like small RNA, named vmiR-5p (for viral miRNA), derived from the SARS-CoV-2 ORF7a transcript. Its abundance ranges from low to moderate as compared to host miRNAs. vmiR-5p functionally associates with Argonaute proteins -- core components of the RNA interference pathway -- leading to downregulation of host transcripts. One such host messenger RNA encodes Basic Leucine Zipper ATF-Like Transcription Factor 2 (BATF2), which is linked to interferon signaling. We demonstrate that vmiR-5p production relies on cellular machinery, yet is independent of Drosha protein, and is enhanced by the presence of a strong and evolutionarily conserved hairpin formed within the ORF7a sequence. Significance statementWe discovered that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) expresses a small viral non-coding RNA, named vmiR-5p (for viral miRNA), derived from the ORF7a transcript. vmiR-5p associates with the cellular RNA interference machinery to regulate host transcripts likely via target silencing. The production of vmiR-5p relies on cellular machinery and the formation of a strong hairpin within ORF7a sequences. This newly-described vmiR-5p may contribute to SARS-CoV-2 pathogenesis and could become a target for therapeutic intervention.

microbiology↗

Identification and evolution of Cas9 tracrRNAs

Cas9 trans-activating CRISPR RNAs (tracrRNAs) form distinct structures essential for target recognition and cleavage and dictate exchangeability between orthologous proteins. As non-coding RNAs that are often apart from the CRISPR array, their identification can be arduous. In this paper, a new bioinformatic method for the detection of Cas9 tracrRNAs is presented. The approach utilizes a co-variance model (CM) based on both sequence homology and predicted secondary structure to locate tracrRNAs. This method predicts a tracrRNA for 98% of CRISPR-Cas9 systems identified by us. The identified tracrRNAs exhibit wide variation in sequence identity, however, CM analyses allow 94.7% to be categorized into just 10 related groups. Finally, association between Cas9 amino acid sequence-based phylogeny and tracrRNA secondary structure is evaluated, revealing strong evidence that secondary structure is evolutionarily conserved among Cas9 lineages. Altogether, our findings provide insight into Cas9 tracrRNA evolution and efforts to characterize the tracrRNA of new Cas9 systems.

evolutionary biology↗