ViennaRNA Package 2.0

Toward Increasing the Credibility of RNA Design

In the problem of RNA design, also known as inverse folding, RNA sequences are predicted that achieve the desired secondary structure at the lowest possible free energy and under certain constraints. The designed sequences have applications in synthetic biology and RNA-based nanotechnologies. There are also known cases of the successful use of inverse folding to discover previously unknown noncoding RNAs. Several computational methods have been dedicated to the problem of RNA design. They differ by algorithm and additional parameters, e.g., those determining the goal function in the sequence optimization process. Users can obtain many promising RNA sequences quite easily. The more difficult issue is to critically evaluate them and select the most favorable and reliable sequence that form1s the expected RNA structure. The latter problem is addressed in this paper. We propose an RNA design protocol extended to include sequence evaluation, for which a 3D structure is used. Experiments show that the accuracy of RNA design can be improved by adding a 3D structure prediction and analysis step.

AptamerRunner: An accessible aptamer structure prediction and clustering algorithm for visualization of selected aptamers

Aptamers are short single-stranded DNA or RNA molecules with high affinity and specificity for targets and are generated using the iterative systematic evolution of ligands by exponential enrichment (SELEX) process. Next-generation sequencing (NGS) revolutionized aptamer selections by allowing a more comprehensive analysis of SELEX-enriched aptamers as compared to Sanger sequencing. The current challenge with aptamer NGS datasets is identifying a diverse cohort of candidate aptamers with the highest likelihood of successful experimental validation. Here we present AptamerRunner, an aptamer sequence and/or structure clustering algorithm that synergistically integrates computational analysis with visualization and expertise-directed decision making. The visual integration of networked aptamers with ranking data, such as fold enrichment or scoring algorithm results, represents a significant advancement over existing clustering tools by providing a natural context to depict groups of aptamers from which ranked or scored candidates can be chosen for experimental validation. The inherent flexibility, user-friendly design, and prospects for future enhancements with AptamerRunner have broad-reaching implications for aptamer researchers across a wide range of disciplines.

A statistical-physics approach for codon usage optimisation

The concept of "codon optimisation" involves adjusting the coding sequence of a target protein to account for the inherent codon preferences of a host species and maximise protein expression in that species. However, there is still a lack of consensus on the most effective approach to achieve optimal results. Existing methods typically depend on heuristic combinations of different variables, leaving the user with the final choice of the sequence hit. In this study, we propose a new statistical-physics model for codon optimisation. This model, called the Nearest-Neighbour interaction (NN) model, links the probability of any given codon sequence to the "interactions" between neighbouring codons. We used the model to design codon sequences for different proteins of interest, and we compared our sequences with the predictions of some commercial tools. In order to assess the importance of the pair interactions, we additionally compared the NN model with a simpler method (Ind) that disregards interactions. It was observed that the NN method yielded similar Codon Adaptation Index (CAI) values to those obtained by other commercial algorithms, despite the fact that CAI was not explicitly considered in the algorithm. By utilising both the NN and Ind methods to optimise the reporter protein luciferase, and then analysing the translation performance in human cell lines and in a mouse model, we found that the NN approach yielded the highest protein expression in vivo. Consequently, we propose that the NN model may prove advantageous in biotechnological applications, such as heterologous protein expression or mRNA-based therapies.

In silico identification of novel pre-microRNA genes in Rift valley fever virus suggest new pathomechanisms for embryo-fetal dysgenesis

MicroRNAs (miRNAs) are small non-coding RNAs that regulate the post-transcriptional expression of target genes. Virus-encoded miRNAs play an important role in the replication of viruses, modulate gene expression in both the virus and host, and affect their persistence and immune evasion in hosts. This renders viral miRNAs as potential targets for therapeutic applications, especially against pathogenic viruses that infect humans and animals. Rift Valley fever virus (RVFV) is a mosquito-borne zoonotic RNA virus that causes severe disease in both humans and livestock. High mortality among newborn lambs and abortion storms are key characteristics of an RVF outbreak. To date, limited information is available on RVFV-derived miRNAs. In this study, computational methods were used to analyse the RVFV genome for putative pre-miRNA genes, which were then analysed for the presence of mature miRNAs. We detected 19 RVFV-encoded miRNAs and identified their potential mRNAs targets in sheep (Ovis aries), the most susceptible host. The identification of significantly enriched O. aries genes in association with RVFV miRNAs will help elucidate the molecular mechanisms underlying RVFV pathogenesis and potentially uncover novel drug targets for RVFV.

Human lncRNAs harbor conserved modules embedded in different sequence contexts

We analyzed the structure of human long non-coding RNA (lncRNAs) genes to investigate whether the non-coding transcriptome is organized in modular domains, as is the case for protein-coding genes. To this aim, we compared all known human lncRNA exons and identified 340 pairs of exons with high sequence and/or secondary structure similarity but embedded in a dissimilar sequence context. We grouped these pairs in 106 clusters based on their reciprocal similarities. These shared modules are highly conserved between humans and the four great ape species, display evidence of purifying selection and likely arose as a result of recent segmental duplications. Our analysis contributes to the understanding of the mechanisms driving the evolution of the non-coding genome and suggests additional strategies towards deciphering the functional complexity of this class of molecules.

The design and engineering of synthetic genomes

Synthetic genomics seeks to design and construct entire genomes to mechanistically dissect fundamental questions of genome function and to engineer organisms for diverse applications, including bioproduction of high-value chemicals and biologics, advanced cell therapies, and stress-tolerant crops. Recent progress has been fuelled by advancements in DNA synthesis, assembly, delivery and editing. Computational innovations, such as the use of artificial intelligence to provide prediction of function, also provide increasing capabilities to guide synthetic genome design and construction. However, translating synthetic genome-scale projects from idea to implementation remains highly complex. Here, we aim to streamline this implementation process by comprehensively reviewing the strategies for design, construction, delivery, debugging and tailoring of synthetic genomes as well as their potential applications.

Deep generative design of RNA aptamers using structural predictions

RNAs represent a class of programmable biomolecules capable of performing diverse biological functions. Recent studies have developed accurate RNA three-dimensional structure prediction methods, which may enable new RNAs to be designed in a structure-guided manner. Here, we develop a structure-to-sequence deep learning platform for the de novo generative design of RNA aptamers. We show that our approach can design RNA aptamers that are predicted to be structurally similar, yet sequence dissimilar, to known light-up aptamers that fluoresce in the presence of small molecules. We experimentally validate several generated RNA aptamers to have fluorescent activity, show that these aptamers can be optimized for activity in silico, and find that they exhibit a mechanism of fluorescence similar to that of known light-up aptamers. Our results demonstrate how structural predictions can guide the targeted and resource-efficient design of new RNA sequences.

ALS-associated FUS mutation reshapes the RNA and protein composition of stress granules

Stress granules (SG) are part of a cellular protection mechanism where untranslated messenger RNAs and RNA-binding proteins are stored upon conditions of cellular stress. Compositional variations due to qualitative or quantitative protein changes can disrupt their functionality and alter their structure. This is the case of different forms of amyotrophic lateral sclerosis (ALS) where a causative link has been proposed between the cytoplasmic de-localization of mutant proteins, such as FUS (Fused in Sarcoma), and the formation of cytotoxic inclusions. Here, we describe the SG transcriptome in neuroblastoma cells and define several features for RNA recruitment in these condensates. We demonstrate that SG dynamics and RNA content are strongly modified by the incorporation of mutant FUS, switching to a more unstructured, AU-rich SG transcriptome. Moreover, we show that mutant FUS, together with its protein interactors and their target RNAs, are responsible for the reshaping of the mutant SG transcriptome with alterations that can be linked to neurodegeneration. Our data describe the molecular differences between physiological and pathological SG in ALS-FUS conditions, showing how FUS mutations impact the RNA and protein composition of these condensates.

Ageing-associated long non-coding RNA extends lifespan and reduces translation in non-dividing cells

Genomes produce widespread long non-coding RNAs (lncRNAs) of largely unknown functions. We characterize aal1 (ageing-associated lncRNA), which is induced in quiescent fission yeast cells. Deletion of aal1 shortens the chronological lifespan of non-dividing cells, while ectopic overexpression prolongs their lifespan, indicating that aal1 acts in trans. Overexpression of aal1 represses ribosomal-protein gene expression and inhibits cell growth, and aal1 genetically interacts with coding genes functioning in protein translation. The aal1 lncRNA localizes to the cytoplasm and associates with ribosomes. Notably, aal1 overexpression decreases the cellular ribosome content and inhibits protein translation. The aal1 lncRNA binds to the rpl1901 mRNA, encoding a ribosomal protein. The rpl1901 levels are reduced ~2-fold by aal1, which is sufficient to extend lifespan. Remarkably, the expression of the aal1 lncRNA in Drosophila boosts fly lifespan. We propose that aal1 reduces the ribosome content by decreasing Rpl1901 levels, thus attenuating the translational capacity and promoting longevity. Although aal1 is not conserved, its effect in flies suggests that animals feature related mechanisms that modulate ageing, based on the conserved translational machinery.

SCAR-6 elncRNA locus epigenetically regulates PROZ and modulates coagulation and vascular function

In this study, we characterize a novel lncRNA-producing gene locus that we name Syntenic Cardiovascular Conserved Region-Associated lncRNA-6 (scar-6) and functionally validate its role in coagulation and cardiovascular function. A 12-bp deletion of the scar-6 locus in zebrafish (scar-6gib007Δ12/Δ12) results in cranial hemorrhage and vascular permeability. Overexpression, knockdown and rescue with the scar-6 lncRNA modulates hemostasis in zebrafish. Molecular investigation reveals that the scar-6 lncRNA acts as an enhancer lncRNA (elncRNA), and controls the expression of prozb, an inhibitor of factor Xa, through an enhancer element in the scar-6 locus. The scar-6 locus suppresses loop formation between prozb and scar-6 sequences, which might be facilitated by the methylation of CpG islands via the prdm14-PRC2 complex whose binding to the locus might be stabilized by the scar-6 elncRNA transcript. Binding of prdm14 to the scar-6 locus is impaired in scar-6gib007Δ12/Δ12 zebrafish. Finally, activation of the PAR2 receptor in scar-6gib007Δ12/Δ12 zebrafish triggers NF-κB-mediated endothelial cell activation, leading to vascular dysfunction and hemorrhage. We present evidence that the scar-6 locus plays a role in regulating the expression of the coagulation cascade gene prozb and maintains vascular homeostasis.

VCAT: an integrated variant function annotation tools

The development of sequencing technology has promoted discovery of variants in the human genome. Identifying functions of these variants is important for us to link genotype to phenotype, and to diagnose diseases. However, it usually requires researchers to visit multiple databases. Here, we presented a one-stop webserver for variant function annotation tools (VCAT, https://biomed.nscc-gz.cn/zhaolab/VCAT/ ) that is the first one connecting variant to functions via the epigenome, protein, drug and RNA. VCAT is also the first one to make all annotations visualized in interactive charts or molecular structures. VCAT allows users to upload data in VCF format, and download results via a URL. Moreover, VCAT has annotated a huge number (1,262,041,068) of variants collected from dbSNP, 1000 Genomes projects, gnomAD, ICGC, TCGA, and HPRC Pangenome project. For these variants, users are able to searcher their functions, related diseases and drugs from VCAT. In summary, VCAT provides a one-stop webserver to explore the potential functions of human genomic variants including their relationship with diseases and drugs.

Generation of a Vibrio-based platform for efficient conversion of raffinose through Adaptive Laboratory Evolution on a solid medium

Raffinose, a trisaccharide abundantly found in soybeans, is a potential alternative carbon source for biorefineries. Nevertheless, residual intermediate di- or monosaccharides and low catabolic efficiency limit raffinose use through conventional microbial hosts. This study presents a Vibrio-based platform to convert raffinose efficiently. Vibrio sp. dhg was selected as the starting strain for the Adaptive Laboratory Evolution (ALE) strategy to leverage its significantly higher metabolic efficiency. We conducted ALE on a solid minimal medium supplemented with raffinose to prevent the enrichment of undesired phenotypes due to the shared effect of extracellular raffinose hydrolysis among multiple strains. As a result, we generated the VRA10 strain that efficiently utilizes raffinose without leaving behind degraded di- or monosaccharides, achieving a notable growth rate (0.40 h-1) and raffinose consumption rate (1.2 g/gdcw/h). Whole genome sequencing and reverse engineering identified that a missense mutation in the melB gene (encoding a melibiose/raffinose:sodium symporter) and the deletion of the two galR genes (encoding transcriptional repressors for galactose catabolism) facilitated rapid raffinose utilization. The further engineered strain produced 6.2 g/L of citramalate from 20 g/L of raffinose. This study will pave the way for the efficient utilization of diverse raffinose-rich byproducts and the expansion of alternative carbon streams in biorefinery applications.

Diverse anti-defence systems are encoded in the leading region of plasmids

Plasmids are major drivers of gene mobilization by means of horizontal gene transfer and play a key role in spreading antimicrobial resistance among pathogens1,2. Despite various bacterial defence mechanisms such as CRISPR-Cas, restriction-modification systems and SOS-response genes that prevent the invasion of mobile genetic elements3, plasmids robustly transfer within bacterial populations through conjugation4,5. Here we show that the leading region of plasmids, the first to enter recipient cells, is a hotspot for an extensive repertoire of anti-defence systems, encoding anti-CRISPR, anti-restriction, anti-SOS and other counter-defence proteins. We further identified in the leading region a prevalence of promoters known to allow expression from single-stranded DNA6, potentially facilitating rapid protection against bacterial immunity during the early stages of plasmid establishment. We demonstrated experimentally the importance of anti-defence gene localization in the leading region for efficient conjugation. These results indicate that focusing on the leading region of plasmids could lead to the discovery of diverse anti-defence genes. Combined, our findings show a new facet of plasmid dissemination and provide theoretical foundations for developing efficient conjugative delivery systems for natural microbial communities.

Decoding the Role of NEIL1 Gene in DNA Repair and Lifespan: A Literature Review with Bioinformatics Analysis

Longevity, the length of an organism's lifespan, is impacted by environmental factors, metabolic processes, and genetic determinants. The base excision repair (BER) pathway is crucial for maintaining genomic integrity by repairing oxidatively modified base lesions. Nei-like DNA Glycosylase 1 (NEIL1), part of the BER pathway, is vital in repairing oxidative bases in G-rich DNA regions, such as telomeres and promoters. Hence, in this comprehensive review, it have undertaken a meticulous investigation of the intricate association between NEIL1 and longevity. The analysis delves into the multifaceted aspects of the NEIL1 gene, its various RNA transcripts, and the diverse protein isoforms. In addition, a combination of bioinformatic analysis is conducted to identify NEIL1 mutations, transcription factors, and epigenetic modifications, as well as its lncRNA/pseudogene/circRNA-miRNA-mRNA regulatory network. The findings suggest that the normal function of NEIL1 is a significant factor in human health and longevity, with defects in NEIL1 potentially leading to various cancers and related syndromes, Alzheimer's disease, obesity, and diabetes.

Targeting RNA with small molecules, from RNA structures to precision medicines: IUPHAR review: 40

RNA plays important roles in regulating both health and disease biology in all kingdoms of life. Notably, RNA can form intricate three-dimensional structures, and their biological functions are dependent on these structures. Targeting the structured regions of RNA with small molecules has gained increasing attention over the past decade, because it provides both chemical probes to study fundamental biology processes and lead medicines for diseases with unmet medical needs. Recent advances in RNA structure prediction and determination and RNA biology have accelerated the rational design and development of RNA-targeted small molecules to modulate disease pathology. However, challenges remain in advancing RNA-targeted small molecules towards clinical applications. This review summarizes strategies to study RNA structures, to identify small molecules recognizing these structures, and to augment the functionality of RNA-binding small molecules. We focus on recent advances in developing RNA-targeted small molecules as potential therapeutics in a variety of diseases, encompassing different modes of actions and targeting strategies. Furthermore, we present the current gaps between early-stage discovery of RNA-binding small molecules and their clinical applications, as well as a roadmap to overcome these challenges in the near future.

Wfold: A new method for predicting RNA secondary structure with deep learning

Precise estimations of RNA secondary structures have the potential to reveal the various roles that non-coding RNAs play in regulating cellular activity. However, the mainstay of traditional RNA secondary structure prediction methods relies on thermos-dynamic models via free energy minimization, a laborious process that requires a lot of prior knowledge. Here, RNA secondary structure prediction using Wfold, an end-to-end deep learning-based approach, is suggested. Wfold is trained directly on annotated data and base-pairing criteria. It makes use of an image-like representation of RNA sequences, which an enhanced U-net incorporated with a transformer encoder can process effectively. Wfold eventually increases the accuracy of RNA secondary structure prediction by combining the benefits of self-attention mechanism's mining of long-range information with U-net's ability to gather local information. We compare Wfold's performance using RNA datasets that are within and across families. When trained and evaluated on different RNA families, it achieves a similar performance as the traditional methods, but dramatically outperforms the state-of-the-art methods on within-family datasets. Moreover, Wfold can also reliably forecast pseudoknots. The findings imply that Wfold may be useful for improving sequence alignment, functional annotations, and RNA structure modeling.

Abundant mRNA m1A modification in dinoflagellates: a new layer of gene regulation

Dinoflagellates, a class of unicellular eukaryotic phytoplankton, exhibit minimal transcriptional regulation, representing a unique model for exploring gene expression. The biosynthesis, distribution, regulation, and function of mRNA N1-methyladenosine (m1A) remain controversial due to its limited presence in typical eukaryotic mRNA. This study provides a comprehensive map of m1A in dinoflagellate mRNA and shows that m1A, rather than N6-methyladenosine (m6A), is the most prevalent internal mRNA modification in various dinoflagellate species, with an asymmetric distribution along mature transcripts. In Amphidinium carterae, we identify 6549 m1A sites characterized by a non-tRNA T-loop-like sequence motif within the transcripts of 3196 genes, many of which are involved in regulating carbon and nitrogen metabolism. Enriched within 3'UTRs, dinoflagellate mRNA m1A levels negatively correlate with translation efficiency. Nitrogen depletion further decreases mRNA m1A levels. Our data suggest that distinctive patterns of m1A modification might influence the expression of metabolism-related genes through translational control.

Systematic analysis of the target recognition and repression by the Pumilio proteins

RNA binding proteins orchestrate the post-transcriptional fate of RNA molecules, but the principles of their action remain poorly understood. Pumilio (PUM) proteins bind 3' UTRs of mRNAs and lead to mRNA decay. To comprehensively map the determinants of recognition of sequences by PUM proteins in cells and to study the binding outcomes, we developed a massively parallel RNA assay that profiled thousands of PUM-binding sites in cells undergoing various perturbations or RNA immunoprecipitation. By studying fragments from the NORAD long non-coding RNA, we find two features that antagonize repression by PUM proteins - G/C rich sequences, particularly those upstream of the PUM recognition element, and binding of FAM120A, which limits the repression elicited by PUM-binding sites. We also find that arrays of PUM sites separated by 8-12 bases offer particularly strong repression and use them to develop a particularly sensitive reporter for PUM repression. In contrast, PUM sites separated by shorter linkers, such as some of those found in NORAD, exhibit strong activity interdependence, likely mediated by competition between PUM binding and formation of strong secondary structures. Overall, our findings expand our understanding of the determinants of PUM protein activity in human cells.

Advancing microRNA target site prediction with transformer and base-pairing patterns

MicroRNAs (miRNAs) are short non-coding RNAs involved in various cellular processes, playing a crucial role in gene regulation. Identifying miRNA targets remains a central challenge and is pivotal for elucidating the complex gene regulatory networks. Traditional computational approaches have predominantly focused on identifying miRNA targets through perfect Watson-Crick base pairings within the seed region, referred to as canonical sites. However, emerging evidence suggests that perfect seed matches are not a prerequisite for miRNA-mediated regulation, underscoring the importance of also recognizing imperfect, or non-canonical, sites. To address this challenge, we propose Mimosa, a new computational approach that employs the Transformer framework to enhance the prediction of miRNA targets. Mimosa distinguishes itself by integrating contextual, positional and base-pairing information to capture in-depth attributes, thereby improving its predictive capabilities. Its unique ability to identify non-canonical base-pairing patterns makes Mimosa a standout model, reducing the reliance on pre-selecting candidate targets. Mimosa achieves superior performance in gene-level predictions and also shows impressive performance in site-level predictions across various non-human species through extensive benchmarking tests. To facilitate research efforts in miRNA targeting, we have developed an easy-to-use web server for comprehensive end-to-end predictions, which is publicly available at http://monash.bioweb.cloud.edu.au/Mimosa.

Sarbecovirus programmed ribosome frameshift RNA element folding studied by NMR spectroscopy and comparative analyses

The programmed ribosomal frameshift (PRF) region is found in the RNA genome of all coronaviruses and shifts the ribosome reading frame through formation of a three-stem pseudoknot structure, allowing the translation of essential viral proteins. Using NMR spectroscopy, comparative sequence analyses and functional assays we show that, in the absence of the ribosome, a 123-nucleotide sequence encompassing the PRF element of SARS-CoV-2 adopts a well-defined two-stem loop structure that is conserved in all SARS-like coronaviruses. In this conformation, the attenuator hairpin and slippery site nucleotides are exposed in the first stem-loop and two pseudoknot stems are present in the second stem-loop, separated by an 8-nucleotide bulge. Formation of the third pseudoknot stem depends on pairing between bulge nucleotides and base-paired nucleotides of the upstream stem-loop, as shown by a PRF construct where residues of the upstream stem were removed, which formed the pseudoknot structure and had increased frameshifting activity in a dual-luciferase assay. The base-pair switch driving PRF pseudoknot folding was found to be conserved in several human non-SARS coronaviruses. The collective results suggest that the frameshifting pseudoknot structure of these viruses only forms transiently in the presence of the translating ribosome. These findings clarify the frameshifting mechanism in coronaviruses and can have a beneficial impact on antiviral drug discovery.

First description of novel compound heterozygous mutations in HYCC1: clinical evaluations and molecular analysis in patient with hypomyelinating leukodystrophy-5 with retrospective view

Hypomyelinating leukodystrophy-5 (HLD5) is a rare autosomal recessive hypomyelination disorder characterized by congenital cataract, progressive neurologic impairment, and myelin deficiency in the central and peripheral nervous system, caused by mutations in the HYCC1 gene. Here we report a 23-year-old girl with HLD5 from unrelated families. Molecular analysis was performed using sequence screening of the HYCC1 gene. In addition, in silico prediction tools and molecular investigation were used to predict the structural effect of the mutations. Results showed a novel compound heterozygous mutation in the HYCC1 gene. Moreover, in silico tools and 3D structural modeling revealed that c.521C > A (p.Ala174Glu) and c.652C > G (p.Gln218Glu) mutations could affect the structure, stability, and conformational analyses in the N-ter domain of the Hyccin protein. We also, we compared the phenotype of our patient with those of previously reported cases with HLD5 syndrome and our findings indicate the absence of reliable genotype-phenotype correlations. To the best of our knowledge, this is the first report describing a Tunisian HLD5 patient with compound heterozygous mutations (c.521C > A (p.Ala174Glu) and c.652C > G (p.Gln218Glu)) in HYCC1 gene.

RPS 2.0: an updated database of RNAs involved in liquid-liquid phase separation

Liquid-liquid phase separation (LLPS) is a crucial process for the formation of biomolecular condensates such as coacervate droplets, P-bodies and stress granules, which play critical roles in many physiological and pathological processes. Increasing studies have shown that not only proteins but also RNAs play a critical role in LLPS. To host LLPS-associated RNAs, we previously developed a database named 'RPS' in 2021. In this study, we present an updated version RPS 2.0 (https://rps.renlab.cn/) to incorporate the newly generated data and to host new LLPS-associated RNAs driven by post-transcriptional regulatory mechanisms. Currently, RPS 2.0 hosts 171 301 entries of LLPS-associated RNAs in 24 different biomolecular condensates with four evidence types, including 'Reviewed', 'High-throughput (LLPS enrichment)', 'High-throughput (LLPS perturbation)' and 'Predicted', and five event types, including 'Expression', 'APA', 'AS', 'A-to-I' and 'Modification'. Additionally, extensive annotations of LLPS-associated RNAs are provided in RPS 2.0, including RNA sequence and structure features, RNA-protein/RNA-RNA interactions, RNA modifications, as well as diseases related annotations. We expect that RPS 2.0 will further promote research of LLPS-associated RNAs and deepen our understanding of the biological functions and regulatory mechanisms of LLPS.

The oral pathogen Porphyromonas gingivalis gains tolerance to the antimicrobial peptide DGL13K by synonymous mutations in hagA

Porphyromonas gingivalis is a keystone pathogen for periodontal disease. The bacteria are black-pigmented and require heme for growth. P. gingivalis exhibit resistance to many antimicrobial peptides, which contributes to their success in the oral cavity. P. gingivalis W50 was resistant to the antimicrobial peptide LGL13K but susceptible to the all-D-amino acid stereoisomer, DGL13K. Upon prolonged exposure to DGL13K, a novel non-pigmented mutant was isolated. Exposure to the L-isomer, LGL13K, did not produce a non-pigmented mutant. The goal of this study was to characterize the genomic and cellular changes that led to the non-pigmented phenotype upon treatment with DGL13K. The non-pigmented mutant showed a low minimum inhibitory concentration and two-fold extended minimum duration for killing by DGL13K, consistent with tolerance to this peptide. The DGL13K-tolerant bacteria exhibited synonymous mutations in the hagA gene. The mutations did not prevent mRNA expression but were predicted to alter mRNA structure. The non-pigmented bacteria were deficient in hemagglutination and hemoglobin binding, suggesting that the HagA protein was not expressed. This was supported by whole cell enzyme-linked immunosorbent assay and gingipain activity assays, which suggested the absence of HagA but not of two closely related gingipains. In vivo virulence was similar for wild type and non-pigmented bacteria in the Galleria mellonella model. The results suggest that, unlike LGL13K, DGL13K can defeat multiple bacterial resistance mechanisms but bacteria can gain tolerance to DGL13K through mutations in the hagA gene.

Designing novel multiepitope mRNA vaccine targeting Hendra virus (HeV): An integrative approach utilizing immunoinformatics, reverse vaccinology, and molecular dynamics simulation

Human and animal health is threatened by Hendra virus (HeV), which has few treatments. This in-silico vaccine design study focuses on HeV G (glycoprotein), F (fusion protein), and M (matrix protein). These proteins were computationally assessed for B and T-cell epitopes after considering HeV strain conservation, immunogenicity, and antigenicity. To improve vaccination immunogenicity, these epitopes were selectively ligated into a multiepitope construct. To improve vaccination longevity and immunological response, adjuvants and linkers were ligated. G, F, and M epitopes were used to create an mRNA HeV vaccine. Cytotoxic, helper, and linear B-lymphocytes' epitopes are targeted by this vaccine. The population coverage analysis demonstrates that multi-epitope vaccination covers 91.81 percent of CTL and 98.55 percent of HTL epitopes worldwide. GRAVY evaluated the vaccine's well-characterized physicochemical properties -0.503, indicating solubility and functional stability. Structure analysis showed well-stabilized 2° and 3° structures in the vaccine, with alpha helix, beta sheet, and coil structures (Ramachandran score of 88.5% and Z score of -3.44). There was a strong affinity as shown by docking tests with TLR-4 (central score of -1139.4 KJ/mol) and TLR-2 (center score of -1277.9 KJ/mol). The coupled V-apo, V-TLR2, and V-TLR4 complexes were tested for binding using molecular dynamics simulation where extremely stable complexes were found. The predicted mRNA structures provided significant stability. Codon optimization for Escherichia. coli synthesis allowed the vaccine to attain a GC content of 46.83% and a CAI score of 1.0, which supports its significant expression. Immunological simulations indicated vaccine-induced innate and adaptive immune reactions. Finally, this potential HeV vaccine needs more studies to prove its efficacy and safety.

Viroid-like colonists of human microbiomes

Here, we describe "obelisks," a class of heritable RNA elements sharing several properties: (1) apparently circular RNA ∼1 kb genome assemblies, (2) predicted rod-like genome-wide secondary structures, and (3) open reading frames encoding a novel "Oblin" protein superfamily. A subset of obelisks includes a variant hammerhead self-cleaving ribozyme. Obelisks form their own phylogenetic group without detectable similarity to known biological agents. Surveying globally, we identified 29,959 distinct obelisks (clustered at 90% sequence identity) from diverse ecological niches. Obelisks are prevalent in human microbiomes, with detection in ∼7% (29/440) and ∼50% (17/32) of queried stool and oral metatranscriptomes, respectively. We establish Streptococcus sanguinis as a cellular host of a specific obelisk and find that this obelisk's maintenance is not essential for bacterial growth. Our observations identify obelisks as a class of diverse RNAs of yet-to-be-determined impact that have colonized and gone unnoticed in human and global microbiomes.

Loss of Diphthamide Increases DNA Replication Stress in Mammalian Cells by Modulating the Translation of RRM1

Diphthamide (DPH) is a highly conserved post-translational modification exclusively present in eukaryotic translation elongation factor 2 (eEF2), with its loss leading to embryonic lethality in mice and developmental disorders in humans. In this study, we unveil the role of diphthamide in mammalian cell DNA damage stress, with a particular emphasis on DNA replication stress. We developed a systematic strategy to identify human proteins affected by diphthamide with a combination of computational profiling and quantitative proteomics. Through this approach, we determine that the translation of RRM1 is modulated by diphthamide via -1 frameshifting. Importantly, our results reveal that the dysregulation of RRM1 translation in DPH-deficient cells is causally linked to elevated DNA replication stress. These findings provide a potential explanation for how diphthamide deficiency leads to cancer and developmental defects in humans.

CRISPR-GRIT: Guide RNAs with Integrated Repair Templates Enable Precise Multiplexed Genome Editing in the Diploid Fungal Pathogen Candida albicans

Candida albicans, an opportunistic fungal pathogen, causes severe infections in immunocompromised individuals. Limited classes and overuse of current antifungals have led to the rapid emergence of antifungal resistance. Thus, there is an urgent need to understand fungal pathogen genetics to develop new antifungal strategies. Genetic manipulation of C. albicans is encumbered by its diploid chromosomes requiring editing both alleles to elucidate gene function. Although the recent development of CRISPR-Cas systems has facilitated genome editing in C. albicans, large-scale and multiplexed functional genomic studies are still hindered by the necessity of cotransforming repair templates for homozygous knockouts. Here, we present CRISPR-GRIT (Guide RNAs with Integrated Repair Templates), a repair template-integrated guide RNA design for expedited gene knockouts and multiplexed gene editing in C. albicans. We envision that this method can be used for high-throughput library screens and identification of synthetic lethal pairs in both C. albicans and other diploid organisms with strong homologous recombination machinery.

A measles virus collective infectious unit that caused lethal human brain disease includes many locally restricted and few widespread copy-back defective genomes

During virus replication in cultured cells, copy-back defective viral genomes (cbDVGs) can arise. CbDVGs are powerful inducers of innate immune responses in vitro, but their occurrence and impact on natural infections of human hosts remain poorly defined. We asked whether cbDVGs were generated in the brain of a patient who succumbed to subacute sclerosing panencephalitis (SSPE) about 20 years after acute measles virus (MeV) infection. Previous analyses of 13 brain specimens of this patient indicated that a collective infectious unit (CIU) drove lethal MeV spread. In this study, we identified 276 replication-competent cbDVG species, each present in over 100 copies in the brain. Six species were detected in multiple forebrain locations, implying that they travelled long-distance with the CIU. The cbDVG to full-length genomes ratio was often close to 1 (0.6-1.74). Most cbDVGs were 324-2,000 bases in length, corresponding to 2%-12% of the full-length genome; all are predicted to have complementary terminal sequences. If improperly encapsidated, these sequences have the potential to form double-stranded structures that can induce innate immune responses. To assess this, we examined the transcriptome of all brain specimens. Several interferon and inflammatory response genes were upregulated, but upregulation levels did not correlate with cbDVG levels in the specimens. Thus, the CIU that drove MeV pathogenesis in this brain includes, in addition to two complementary full-length genome populations, many locally restricted and few widespread cbDVG species. The widespread cbDVG species may have been positively selected but how they impacted pathogenesis remains to be determined.IMPORTANCECopy-back defective viral genomes (cbDVGs) can drive virus-host interactions. They can suppress virus replication directly, by competing with full-length genomes, or indirectly by stimulating antiviral immunity. In vitro, cbDVG can slow down infections and promote persistence, but there is limited documentation of their presence in human hosts or of their impact on disease. We had the unique opportunity to analyze the brain of a patient who succumbed to subacute sclerosing panencephalitis, a rare but lethal consequence of measles. We detected more than 270 distinct cbDVG species; most were restricted to one specimen, but several reached all lobes of the forebrain, suggesting positive selection. Our analyses provide the missing knowledge of the diversity of cbDVG in a natural infection of a human host. They also reveal that a collective infectious unit that caused lethal human brain disease includes few widespread cbDVG, in addition to two ubiquitous complementary full-length genome populations.

Engineered mRNAs With Stable Structures Minimize Double-stranded RNA Formation and Increase Protein Expression

The therapeutic use of synthetic message RNA (mRNA) has been validated in COVID-19 vaccines and shows enormous potential in developing infectious and oncological vaccines. However, double-stranded RNA (dsRNA) byproducts generated during the in vitro transcription (IVT) process can diminish the efficacy of mRNA-based therapeutics and provoke innate immune responses. Existing methods to eliminate dsRNA byproducts are often cumbersome and labor-intensive. In this study, we revealed that a loose mRNA secondary structure and more unpaired U bases in the sequence generally lead to the formation of more dsRNA byproducts during the IVT process. We further developed a predictive model for dsRNA byproducts formation based on sequence characteristics to guide the optimization of mRNA sequences, helping to minimize unwanted immune response and improve the protein expression of mRNA products. Collectively, our study provides novel clues and methodologies for developing effective mRNA therapeutics with minimized dsRNA byproducts and increased protein expression.

Determinants of selectivity in the dicing mechanism

Our research elucidates the cleavage processes of the RNase III enzyme, DICER, which plays a crucial role in the production of small RNAs, such as microRNAs (miRNAs) and small interfering RNAs (siRNAs). Utilizing high-throughput dicing assays, we expose the bipartite pairing rule that dictates the cleavage sites of DICER. Furthermore, we decode the intricate recognition mechanism of the primary YCR motif and identify an analogous secondary YCR motif that influences DICER's cleavage choices. Collectively, our findings clarify the bipartite pairing rule and enhance our understanding of the role of RNA motifs in modulating DICER's cleavage activity, laying the groundwork for future research on their roles in miRNA biogenesis and gene regulation.

memerna: Sparse RNA Folding Including Coaxial Stacking

Determining RNA secondary structure is a core problem in computational biology. Fast algorithms for predicting secondary structure are fundamental to this task.Department of Biochemistry & Biophysics, University of Rochester Medical Center, Rochester, NY, USA We describe a modified formulation of the Zuker-Stiegler algorithm with coaxial stacking, a stabilising interaction in which the ends of helices in multi-loops are stacked. In particular, optimal coaxial stacking is computed as part of the dynamic programming state, rather than in an inner loop. We introduce a new notion of sparsity, which we call replaceability. Replaceability is a more general condition and applicable in more places than the triangle inequality that is used by previous sparse folding methods. We also introduce non-monotonic candidate lists as an additional sparsification tool. Existing usages of the triangle inequality for sparsification can be thought of as an application of both replaceability and monotonicity together. The modified recurrences along with replaceability allows sparsification to be applied to coaxial stacking as well, which increases the speed of the algorithm. We implemented this algorithm in software we call memerna, which we show to have the fastest exact (non-heuristic) implementation of RNA folding under the complete Turner 2004 model with coaxial stacking, out of several popular RNA folding tools supporting coaxial stacking. We also introduce a new notation for secondary structure which includes coaxial stacking, terminal mismatches, and dangles (CTDs) information. The memerna package 0.1 release is available at https://github.com/Edgeworth/memerna/tree/release/0.1.

Engineering acyclovir-induced RNA nanodevices for reversible and tunable control of aptamer function

Small molecule-regulated RNA devices have the potential to modulate diverse aspects of cellular function, but the small molecules used to date have potential toxicities limiting their use in cells. Here we describe a method for creating drug-regulated RNA nanodevices (RNs) using acyclovir, a biologically compatible small molecule with minimal toxicity. Our modular approach involves a scaffold comprising a central F30 three-way junction, an integrated acyclovir aptamer on the input arm, and a variable effector-binding aptamer on the output arm. This design allows for the rapid engineering of acyclovir-regulated RNs, facilitating temporal, tunable, and reversible control of intracellular aptamers. We demonstrate the control of the Broccoli aptamer and the iron-responsive element (IRE) by acyclovir. Regulating the IRE with acyclovir enables precise control over iron-regulatory protein (IRP) sequestration, consequently promoting the inhibition of ferroptosis. Overall, the method described here provides a platform for transforming aptamers into acyclovir-controllable antagonists against physiologic target proteins.

miRNASNP-v4: a comprehensive database for miRNA-related SNPs across 17 species

Single nucleotide polymorphisms (SNPs) within microRNAs (miRNAs) and their target binding sites can influence miRNA biogenesis and target regulation, thereby participating in a variety of diseases and biological processes. Current miRNA-related SNP databases are often species-limited or based on outdated data. Therefore, we updated our miRNASNP database to version 4 by updating data, expanding the species from Homo sapiens to 17 species, and introducing several new features. In miRNASNP-v4, 82 580 SNPs in miRNAs and 24 836 179 SNPs in 3'UTRs of genes across 17 species were identified and their potential effects on miRNA secondary structure and target binding were characterized. In addition, compared to the last release, miRNASNP-v4 includes the following improvements: (i) gene enrichment analysis for gained or lost miRNA target genes; (ii) identification of miRNA-related SNPs associated with drug response and immune infiltration in human cancers; (iii) inclusion of experimentally supported immune-related miRNAs and (iv) online prediction tools for 17 animal species. With the extensive data and user-friendly web interface, miRNASNP-v4 will serve as an invaluable resource for functional studies of SNPs and miRNAs in multiple species. The database is freely accessible at http://gong_lab.hzau.edu.cn/miRNASNP/.

Genome-Wide Transcriptional Response of Avocado to Fusarium sp. Infection

The avocado crop is relevant for its economic importance and because of its unique evolutionary history. However, there is a lack of information regarding the molecular processes during the defense response against fungal pathogens. Therefore, using a genome-wide approach in this work, we investigated the transcriptional response of the Mexican horticultural race of avocado (Persea americana var. drymifolia), including miRNAs profile and their possible targets. For that, we established an avocado-Fusarium hydroponic pathosystem and studied the response for 21 days. To guarantee robustness in the analysis, first, we improved the avocado genome assembly available for this variety, resulting in 822.49 Mbp in length with 36,200 gene models. Then, using an RNA-seq approach, we identified 13,778 genes differentially expressed in response to the Fusarium infection. According to their expression profile across time, these genes can be clustered into six groups, each associated with specific biological processes. Regarding non-coding RNAs, 8 of the 57 mature miRNAs identified in the avocado genome are responsive to infection caused by Fusarium, and the analysis revealed a total of 569 target genes whose transcript could be post-transcriptionally regulated. This study represents the first research in avocados to comprehensively explore the role of miRNAs in orchestrating defense responses against Fusarium spp. Also, this work provides valuable data about the genes involved in the intricate response of the avocado during fungal infection.

Dynamics of diversified A-to-I editing in Streptococcus pyogenes is governed by changes in mRNA stability

Adenosine-to-inosine (A-to-I) RNA editing plays an important role in the post-transcriptional regulation of eukaryotic cell physiology. However, our understanding of the occurrence, function and regulation of A-to-I editing in bacteria remains limited. Bacterial mRNA editing is catalysed by the deaminase TadA, which was originally described to modify a single tRNA in Escherichia coli. Intriguingly, several bacterial species appear to perform A-to-I editing on more than one tRNA. Here, we provide evidence that in the human pathogen Streptococcus pyogenes, tRNA editing has expanded to an additional tRNA substrate. Using RNA sequencing, we identified more than 27 editing sites in the transcriptome of S. pyogenes SF370 and demonstrate that the adaptation of S. pyogenes TadA to a second tRNA substrate has also diversified the sequence context and recoding scope of mRNA editing. Based on the observation that editing is dynamically regulated in response to several infection-relevant stimuli, such as oxidative stress, we further investigated the underlying determinants of editing dynamics and identified mRNA stability as a key modulator of A-to-I editing. Overall, our findings reveal the presence and diversification of A-to-I editing in S. pyogenes and provide novel insights into the plasticity of the editome and its regulation in bacteria.

Glass-like Relaxation Dynamics during the Disorder-to-Order Transition of Viral Nucleocapsids

Nucleocapsid self-assembly is an essential yet elusive step in virus replication. Using time-resolved small-angle X-ray scattering on a model icosahedral ssRNA virus, we reveal a previously unreported kinetic pathway. Initially, RNA-bound capsid subunits rapidly accumulate beyond the stoichiometry of native virions. This is followed by a disorder-to-order transition characterized by glass-like relaxation dynamics and the release of excess subunits. Our molecular dynamics simulations, employing a coarse-grained elastic model, confirm the physical feasibility of self-ordering accompanied by subunit release. The relaxation can be modeled by an exponential integral decay on the mean squared radius of gyration, with relaxation times varying within the second range depending on RNA type and subunit concentration. A nanogel model suggests that the initially disordered nucleoprotein complexes quickly reach an equilibrium size, while their mass fractal dimension continues to evolve. Understanding virus self-assembly is not only crucial for combating viral infections, but also for designing synthetic virus-inspired nanocages for drug delivery applications.

Plant lncRNA-miRNA Interaction Prediction Based on Counterfactual Heterogeneous Graph Attention Network

Identifying interactions between long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) provides a new perspective for understanding regulatory relationships in plant life processes. Recently, computational methods based on graph neural networks (GNNs) have been widely employed to predict lncRNA-miRNA interactions (LMIs), which compensate for the inadequacy of biological experiments. However, the low-semantic and noise of graph limit the performance of existing GNN-based methods. In this paper, we develop a novel Counterfactual Heterogeneous Graph Attention Network (CFHAN) to improve the robustness to against the noise and the prediction of plant LMIs. Firstly, we construct a real-world based lncRNA-miRNA (L-M) heterogeneous network. Secondly, CFHAN utilizes the node-level attention, the semantic-level attention, and the counterfactual links to enhance the node embeddings learning. Finally, these embeddings are used as inputs for Multilayer Perceptron (MLP) to predict the interactions between lncRNAs and miRNAs. Evaluating our method on a benchmark dataset of plant LMIs, CFHAN outperforms five state-of-the-art methods, and achieves an average AUC and average ACC of 0.9953 and 0.9733, respectively. This demonstrates CFHAN's ability to predict plant LMIs and exhibits promising cross-species prediction ability, offering valuable insights for experimental LMI researches.

Enhanced RNA-targeting CRISPR-Cas technology in zebrafish

CRISPR-Cas13 systems are widely used in basic and applied sciences. However, its application has recently generated controversy due to collateral activity in mammalian cells and mouse models. Moreover, its efficiency could be improved in vivo. Here, we optimized transient formulations as ribonucleoprotein complexes or mRNA-gRNA combinations to enhance the CRISPR-RfxCas13d system in zebrafish. We i) used chemically modified gRNAs to allow more penetrant loss-of-function phenotypes, ii) improved nuclear RNA-targeting, and iii) compared different computational models and determined the most accurate to predict gRNA activity in vivo. Furthermore, we demonstrated that transient CRISPR-RfxCas13d can effectively deplete endogenous mRNAs in zebrafish embryos without inducing collateral effects, except when targeting extremely abundant and ectopic RNAs. Finally, we implemented alternative RNA-targeting CRISPR-Cas systems with reduced or absent collateral activity. Altogether, these findings contribute to CRISPR-Cas technology optimization for RNA targeting in zebrafish through transient approaches and assist in the progression of in vivo applications.

Sm-site containing mRNAs can accept Sm-rings and are downregulated in Spinal Muscular Atrophy

Sm-ring assembly is important for the biogenesis, stability, and function of uridine-rich small nuclear RNAs (U snRNAs) involved in pre-mRNA splicing and histone pre-mRNA processing. Sm-ring assembly is cytoplasmic and dependent upon the Sm-site sequence and structural motif, ATP, and Survival motor neuron (SMN) protein complex. While RNAs other than U snRNAs were previously shown to associate with Sm proteins, whether this association follows Sm-ring assembly requirements is unknown. We systematically identified Sm-sites within the human and mouse transcriptomes and assessed whether these sites can accept Sm-rings. In addition to snRNAs, Sm-sites are highly prevalent in the 3' untranslated regions of long messenger RNAs. RNA immunoprecipitation experiments confirm that Sm-site containing mRNAs associate with Sm proteins in the cytoplasm. In modified Sm-ring assembly assays, Sm-site containing RNAs, from either bulk polyadenylated RNAs or those transcribed in vitro , specifically associate with Sm proteins in an Sm-site and ATP-dependent manner. In cell and animal models of Spinal Muscular Atrophy (SMA), mRNAs containing Sm-sites are downregulated, suggesting reduced Sm-ring assembly on these mRNAs may contribute to SMA pathogenesis. Together, this study establishes that Sm-site containing mRNAs can accept Sm-rings and identifies a novel mechanism for Sm proteins in regulation of cytoplasmic mRNAs.

GRAPHICAL ABSTRACT

Multi-omics integration analysis reveals the role of N6-methyladenosine in lncRNA translation during glioma stem cell differentiation

Glioblastoma is one of the most lethal brain diseases in humans. Although recent studies have shown reciprocal interactions between N6-methyladenosine (m6A) modifications and long noncoding RNAs (lncRNAs) in gliomagenesis and malignant progression, the mechanism of m6A-mediated lncRNA translational regulation in glioblastoma remains unclear. Herein, we profiled the transcriptomes, translatomes, and epitranscriptomics of glioma stem cells and differentiated glioma cells to investigate the role of m6A in lncRNA translation comprehensively. We found that lncRNAs with numerous m6A peaks exhibit reduced translation efficiency. Transcript-level expression analysis demonstrates an enrichment of m6A around short open reading frames (sORFs) of translatable lncRNA transcripts. Further comparison analysis of m6A modifications in different RNA regions indicates that m6A peaks downstream of sORFs inhibit lncRNA translation more than those upstream. Observations in glioma-associated lncRNAs H19, LINC00467, and GAS5 further confirm the negative effect of m6A methylation on lncRNA translation. Overall, these findings elucidate the dynamic profiles of the m6A methylome and enhance the understanding of the complexity of lncRNA translational regulation.

De novo gene synthesis by an antiviral reverse transcriptase

Defense-associated reverse transcriptase (DRT) systems perform DNA synthesis to protect bacteria against viral infection, but the identities and functions of their DNA products remain largely unknown. We show that DRT2 systems encode an unprecedented immune pathway that involves de novo gene synthesis through rolling circle reverse transcription of a noncoding RNA (ncRNA). Programmed template jumping on the ncRNA generates a concatemeric cDNA, which becomes double-stranded upon viral infection. This DNA product constitutes a protein-coding, nearly endless open reading frame (neo) gene whose expression leads to potent cell growth arrest, restricting the viral infection. Our work highlights an elegant expansion of genome coding potential through RNA-templated gene creation and challenges conventional paradigms of genetic information encoded along the one-dimensional axis of genomic DNA.

Human papillomavirus-encoded circular RNA circE7 promotes immune evasion in head and neck squamous cell carcinoma

Immune evasion represents a crucial milestone in the progression of cancer and serves as the theoretical foundation for tumor immunotherapy. In this study, we reveal a negative association between Human Papillomavirus (HPV)-encoded circular RNA, circE7, and the infiltration of CD8+ T cells in head and neck squamous cell carcinoma (HNSCC). Both in vitro and in vivo experiments demonstrate that circE7 suppresses the function and activity of T cells by downregulating the transcription of LGALS9, which encodes the galectin-9 protein. The molecular mechanism involves circE7 binding to acetyl-CoA carboxylase 1 (ACC1), promoting its dephosphorylation and thereby activating ACC1. Activated ACC1 reduces H3K27 acetylation at the LGALS9 gene promoter, leading to decreased galectin-9 expression. Notably, galectin-9 interacts with immune checkpoint molecules TIM-3 and PD-1, inhibiting the secretion of cytotoxic cytokines by T cells and promoting T cell apoptosis. Here, we demonstrate a mechanism by which HPV promotes immune evasion in HNSCC through a circE7-driven epigenetic modification and propose a potential immunotherapy strategy for HNSCC that involves the combined use of anti-PD-1 and anti-TIM-3 inhibitors.

Dynamic conformation: Marching toward circular RNA function and application

Circular RNA is a group of covalently closed, single-stranded transcripts with unique biogenesis, stability, and conformation that play distinct roles in modulating cellular functions and also possess a great potential for developing circular RNA-based therapies. Importantly, due to its circular conformation, circular RNA generates distinct intramolecular base pairing that is different from the linear transcript. In this perspective, we review how circular RNA conformation can affect its turnover and modes of action, as well as what factors can modulate circular RNA conformation. We also discuss how understanding circular RNA conformation can facilitate learning about their functions as well as the remaining technological issues to further address their conformation. These efforts will ultimately inform the design of circular RNA-based platforms for biomedical applications.

A specific domain within the 3' untranslated region of Usutu virus confers resistance to the exonuclease ISG20

Usutu virus (USUV) and West Nile virus (WNV) are two closely related emerging mosquito-borne flaviviruses. Their natural hosts are wild birds, but they can also cause severe neurological disorders in humans. Both viruses are efficiently suppressed by type I interferon (IFN), which interferes with viral replication, dissemination, pathogenesis and transmission. Here, we show that the replication of USUV and WNV are inhibited through a common set of IFN-induced genes (ISGs), with the notable exception of ISG20, which USUV is resistant to. Strikingly, USUV was the only virus among all the other tested mosquito-borne flaviviruses that demonstrated resistance to the 3'-5' exonuclease activity of ISG20. Our findings highlight that the intrinsic resistance of the USUV genome, irrespective of the presence of cellular or viral proteins or protective post-transcriptional modifications, relies on a unique sequence present in its 3' untranslated region. Importantly, this genomic region alone can confer ISG20 resistance to a susceptible flavivirus, without compromising its infectivity, suggesting that it could be acquired by other flaviviruses. This study provides new insights into the strategy employed by emerging flaviviruses to overcome host defense mechanisms.

The molecular dissection of TRIM25's RNA-binding mechanism provides key insights into its antiviral activity

TRIM25 is an RNA-binding ubiquitin E3 ligase with central but poorly understood roles in the innate immune response to RNA viruses. The link between TRIM25's RNA binding and its role in innate immunity has not been established. Thus, we utilized a multitude of biophysical techniques to identify key RNA-binding residues of TRIM25 and developed an RNA-binding deficient mutant (TRIM25-m9). Using iCLIP2 in virus-infected and uninfected cells, we identified TRIM25's RNA sequence and structure specificity, that it binds specifically to viral RNA, and that the interaction with RNA is critical for its antiviral activity.

Niacin supplementation in a child with novel MTTN variant m.5670A>G causing early onset mitochondrial myopathy and NAD+ deficiency

Myopathy is a common manifestation in mitochondrial disorders, but the pathomechanisms are still insufficiently studied in children. Here, we report a severe, progressive mitochondrial myopathy in a four-year-old child, who died at eight years. He developed progressive loss of muscle strength with nocturnal hypoventilation and dilated cardiomyopathy. Skeletal muscle showed ragged red fibers and severe combined respiratory chain deficiency. Mitochondrial DNA sequencing revealed a novel m.5670A>G mutation in mitochondrial tRNAAsn (MTTN) with 88 % heteroplasmy in muscle. The proband also had systemic NAD+ deficiency but rescuing this with the NAD+ precursor niacin did not stop disease progression. Targeted metabolomics revealed an overall shift of metabolism towards controls after niacin supplementation, with normalized tryptophan metabolites and lipid-metabolic markers, but most amino acids did not respond to niacin therapy. To conclude, we report a new MTTN mutation, secondary NAD+ deficiency in childhood-onset mitochondrial myopathy with metabolic but meager clinical response to niacin supplementation.

Identification of RNA structures and their roles in RNA functions

The development of high-throughput RNA structure profiling methods in the past decade has greatly facilitated our ability to map and characterize different aspects of RNA structures transcriptome-wide in cell populations, single cells and single molecules. The resulting high-resolution data have provided insights into the static and dynamic nature of RNA structures, revealing their complexity as they perform their respective functions in the cell. In this Review, we discuss recent technical advances in the determination of RNA structures, and the roles of RNA structures in RNA biogenesis and functions, including in transcription, processing, translation, degradation, localization and RNA structure-dependent condensates. We also discuss the current understanding of how RNA structures could guide drug design for treating genetic diseases and battling pathogenic viruses, and highlight existing challenges and future directions in RNA structure research.

Towards a seamless product and process development workflow for recombinant proteins produced by plant molecular farming

Plant molecular farming (PMF) has been promoted as a fast, efficient and cost-effective alternative to bacteria and animal cells for the production of biopharmaceutical proteins. Numerous plant species have been tested to produce a wide range of drug candidates. However, PMF generally lacks a systematic, streamlined and seamless workflow to continuously fill the product pipeline. Therefore, it is currently unable to compete with established platforms in terms of routine, throughput and horizontal integration (the rapid translation of product candidates to preclinical and clinical development). Individual management decisions, limited funding and a lack of qualified production capacity can hinder the execution of such projects, but we also lack suitable technologies for sample handling and data management. This perspectives article will highlight current bottlenecks in PMF and offer potential solutions that combine PMF with existing technologies to build an integrated facility of the future for product development, testing, manufacturing and clinical translation. Ten major bottlenecks have been identified and are discussed in turn: automated cloning and simplified transformation options, reproducibility of bacterial cultivation, bioreactor integration with automated cell handling, options for rapid mid-scale candidate and product manufacturing, interconnection with (group-specific or personalized) clinical trials, diversity of (post-)infiltration conditions, development of downstream processing platforms, continuous process operation, compliance of manufacturing conditions with biosafety regulations, scaling requirements for cascading biomass.

Predicting RNA sequence-structure likelihood via structure-aware deep learning

BACKGROUND

The active functionalities of RNA are recognized to be heavily dependent on the structure and sequence. Therefore, a model that can accurately evaluate a design by giving RNA sequence-structure pairs would be a valuable tool for many researchers. Machine learning methods have been explored to develop such tools, showing promising results. However, two key issues remain. Firstly, the performance of machine learning models is affected by the features used to characterize RNA. Currently, there is no consensus on which features are the most effective for characterizing RNA sequence-structure pairs. Secondly, most existing machine learning methods extract features describing entire RNA molecule. We argue that it is essential to define additional features that characterize nucleotides and specific sections of RNA structure to enhance the overall efficacy of the RNA design process.

RESULTS

We develop two deep learning models for evaluating RNA sequence-secondary structure pairs. The first model, NU-ResNet, uses a convolutional neural network architecture that solves the aforementioned problems by explicitly encoding RNA sequence-structure information into a 3D matrix. Building upon NU-ResNet, our second model, NUMO-ResNet, incorporates additional information derived from the characterizations of RNA, specifically the 2D folding motifs. In this work, we introduce an automated method to extract these motifs based on fundamental secondary structure descriptions. We evaluate the performance of both models on an independent testing dataset. Our proposed models outperform the models from literatures in this independent testing dataset. To assess the robustness of our models, we conduct 10-fold cross validation. To evaluate the generalization ability of NU-ResNet and NUMO-ResNet across different RNA families, we train and test our proposed models in different RNA families. Our proposed models show superior performance compared to the models from literatures when being tested across different independent RNA families.

CONCLUSIONS

In this study, we propose two deep learning models, NU-ResNet and NUMO-ResNet, to evaluate RNA sequence-secondary structure pairs. These two models expand the field of data-driven approaches for learning RNA. Furthermore, these two models provide the new method to encode RNA sequence-secondary structure pairs.

RNAelem: an algorithm for discovering sequence-structure motifs in RNA bound by RNA-binding proteins

Motivation

RNA-binding proteins (RBPs) play a crucial role in the post-transcriptional regulation of RNA. Given their importance, analyzing the specific RNA patterns recognized by RBPs has become a significant research focus in bioinformatics. Deep Neural Networks have enhanced the accuracy of prediction for RBP-binding sites, yet understanding the structural basis of RBP-binding specificity from these models is challenging due to their limited interpretability. To address this, we developed RNAelem, which combines profile context-free grammar and the Turner energy model for RNA secondary structure to predict sequence-structure motifs in RBP-binding regions.

Results

RNAelem exhibited superior detection accuracy compared to existing tools for RNA sequences with structural motifs. Upon applying RNAelem to the eCLIP database, we were not only able to reproduce many known primary sequence motifs in the absence of secondary structures, but also discovered many secondary structural motifs that contained sequence-nonspecific insertion regions. Furthermore, the high interpretability of RNAelem yielded insightful findings such as long-range base-pairing interactions in the binding region of the U2AF protein.

Availability and implementation

The code is available at https://github.com/iyak/RNAelem.