If the 5' cap fits (wear it) - Non-canonical RNA capping.

RNA capping is a prominent RNA modification that influences RNA stability, metabolism, and function. While it was long limited to the study of the most abundant eukaryotic canonical m7G cap, the field recently went through a large paradigm shift with the discovery of non-canonical RNA capping in bacteria and ultimately all domains of life. The repertoire of non-canonical caps has expanded to encompass metabolite caps, including NAD, FAD, CoA, UDP-Glucose, and ADP-ribose, alongside alarmone dinucleoside polyphosphate caps, and methylated phosphate cap-like structures. This review offers an introduction into the field, presenting a summary of the current knowledge about non-canonical RNA caps. We highlight the often still enigmatic biological roles of the caps together with their processing enzymes, focusing on the most recent discoveries. Furthermore, we present the methods used for the detection and analysis of these non-canonical RNA caps and thus provide an introduction into this dynamic new field.

LARP3, LARP7, and MePCE are involved in the early stage of human telomerase RNA biogenesis.

Human telomerase assembly is a highly dynamic process. Using biochemical approaches, we find that LARP3 and LARP7/MePCE are involved in the early stage of human telomerase RNA (hTR) and that their binding to RNA is destabilized when the mature form is produced. LARP3 plays a negative role in preventing the processing of the 3'-extended long (exL) form and the binding of LARP7 and MePCE. Interestingly, the tertiary structure of the exL form prevents LARP3 binding and facilitates hTR biogenesis. Furthermore, low levels of LARP3 promote hTR maturation, increase telomerase activity, and elongate telomeres. LARP7 and MePCE depletion inhibits the conversion of the 3'-extended short (exS) form into mature hTR and the cytoplasmic accumulation of hTR, resulting in telomere shortening. Taken together our data suggest that LARP3 and LARP7/MePCE mediate the processing of hTR precursors and regulate the production of functional telomerase.

Single-cell total-RNA profiling unveils regulatory hubs of transcription factors.

Recent development of RNA velocity uses master equations to establish the kinetics of the life cycle of RNAs from unspliced RNA to spliced RNA (i.e., mature RNA) to degradation. To feed this kinetic analysis, simultaneous measurement of unspliced RNA and spliced RNA in single cells is greatly desired. However, the majority of single-cell RNA-seq chemistry primarily captures mature RNA species to measure gene expressions. Here, we develop a one-step total-RNA chemistry-based single-cell RNA-seq method: snapTotal-seq. We benchmark this method with multiple single-cell RNA-seq assays in their performance in kinetic analysis of cell cycle by RNA velocity. Next, with LASSO regression between transcription factors, we identify the critical regulatory hubs mediating the cell cycle dynamics. We also apply snapTotal-seq to profile the oncogene-induced senescence and identify the key regulatory hubs governing the entry of senescence. Furthermore, from the comparative analysis of unspliced RNA and spliced RNA, we identify a significant portion of genes whose expression changes occur in spliced RNA but not to the same degree in unspliced RNA, indicating these gene expression changes are mainly controlled by post-transcriptional regulation. Overall, we demonstrate that snapTotal-seq can provide enriched information about gene regulation, especially during the transition between cell states.

Controllable self-cleaning FET self-assembled RNA-cleaving DNAzyme based DNA nanotree for culture-free Staphylococcus aureus detection.

Staphylococcus aureus (SA) poses a serious risk to human and animal health, necessitating a low-cost and high-performance analytical platform for point-of-care diagnostics. Cellulose paper-based field-effect transistors (FETs) with RNA-cleaving DNAzymes (RCDs) can fulfill the low-cost requirements, however, its high hydrophilicity and lipophilicity hinder biochemical modification and result in low sensitivity, poor mechanical stability and poor fouling performance. Herein, we proposed a controllable self-cleaning FET to simplify biochemical modification and improve mechanical stability and antifouling performance. Then, we constructed an RCD-based DNA nanotree to significantly enhance the sensitivity for SA detection. For controllable self-cleaning FET, 1 H,1 H,2 H,2 H-perfluorodecyltrimethoxysilane based-polymeric nanoparticles were synthesized to decorate cellulose paper and whole carbon nanofilm wires. O2 plasma was applied to regulate to reduce fluorocarbon chain density, and then control the hydrophobic-oleophobic property in sensitive areas. Because negatively charged DNA affected the sensitivity of semiconducting FETs, three Y-shaped branches with low-cost were designed and applied to synthesize an RCD-based DNA-Nanotree based on similar DNA-origami technology, which further improved the sensitivity. The trunk of DNA-Nanotree was composed of RCD, and the canopy was self-assembled using multiple Y-shaped branches. The controllable self-cleaning FET biosensor was applied for SA detection without cultivation, which had a wide linear range from 1 to 105 CFU/mL and could detect a low value of 1 CFU/mL.

Mitochondrion-to-nucleus communication mediated by RNA export: a survey of potential mechanisms and players across eukaryotes.

The nucleus interacts with the other organelles to perform essential functions of the eukaryotic cell. Mitochondria have their own genome and communicate back to the nucleus in what is known as mitochondrial retrograde response. Information is transferred to the nucleus in many ways, leading to wide-ranging changes in nuclear gene expression and culminating with changes in metabolic, regulatory or stress-related pathways. RNAs are emerging molecules involved in this signalling. RNAs encode precise information and are involved in highly target-specific signalling, through a wide range of processes known as RNA interference. RNA-mediated mitochondrial retrograde response requires these molecules to exit the mitochondrion, a process that is still mostly unknown. We suggest that the proteins/complexes translocases of the inner membrane, polynucleotide phosphorylase, mitochondrial permeability transition pore, and the subunits of oxidative phosphorylation complexes may be responsible for RNA export.

Human red blood cells express the RNA sensor TLR7.

Red blood cells (RBCs) express the nucleic acid-binding toll-like receptor 9 (TLR9) and bind CpG-containing DNA. However, whether human RBCs express other nucleic acid-binding TLRs is unknown. Here we show that human RBCs express the RNA sensor TLR7. TLR7 is present on the red cell membrane and is associated with the RBC membrane protein Band 3. In patients with SARS-CoV2-associated sepsis, TLR7-Band 3 interactions in the RBC membrane are increased when compared with healthy controls. In vitro, RBCs bind synthetic ssRNA and RNA from ssRNA viruses. Thus, RBCs may serve as a previously unrecognized sink for exogenous RNA, expanding the repertoire of non-gas exchanging functions performed by RBCs.

Mudskipper detects combinatorial RNA binding protein interactions in multiplexed CLIP data.

The uncovering of protein-RNA interactions enables a deeper understanding of RNA processing. Recent multiplexed crosslinking and immunoprecipitation (CLIP) technologies such as antibody-barcoded eCLIP (ABC) dramatically increase the throughput of mapping RNA binding protein (RBP) binding sites. However, multiplex CLIP datasets are multivariate, and each RBP suffers non-uniform signal-to-noise ratio. To address this, we developed Mudskipper, a versatile computational suite comprising two components: a Dirichlet multinomial mixture model to account for the multivariate nature of ABC datasets and a softmasking approach that identifies and removes non-specific protein-RNA interactions in RBPs with low signal-to-noise ratio. Mudskipper demonstrates superior precision and recall over existing tools on multiplex datasets and supports analysis of repetitive elements and small non-coding RNAs. Our findings unravel splicing outcomes and variant-associated disruptions, enabling higher-throughput investigations into diseases and regulation mediated by RBPs.

The glycine-rich domain of GRP7 plays a crucial role in binding long RNAs and facilitating phase separation.

Microscale thermophoresis (MST) is a well-established method to quantify protein-RNA interactions. In this study, we employed MST to analyze the RNA binding properties of glycine-rich RNA binding protein 7 (GRP7), which is known to have multiple biological functions related to its ability to bind different types of RNA. However, the exact mechanism of GRP7's RNA binding is not fully understood. While the RNA-recognition motif of GRP7 is known to be involved in RNA binding, the glycine-rich region (known as arginine-glycine-glycine-domain or RGG-domain) also influences this interaction. To investigate to which extend the RGG-domain of GRP7 is involved in RNA binding, mutation studies on putative RNA interacting or modulating sites were performed. In addition to MST experiments, we examined liquid-liquid phase separation of GRP7 and its mutants, both with and without RNA. Furthermore, we systemically investigated factors that might affect RNA binding selectivity of GRP7 by testing RNAs of different sizes, structures, and modifications. Consequently, our study revealed that GRP7 exhibits a high affinity for a variety of RNAs, indicating a lack of pronounced selectivity. Moreover, we established that the RGG-domain plays a crucial role in binding longer RNAs and promoting phase separation.

Characterization of m6A Modifiers and RNA Modifications in Uterine Fibroids.

Uterine leiomyoma or fibroids are prevalent noncancerous tumors of the uterine muscle layer, yet their origin and development remain poorly understood. We analyzed RNA expression profiles of 15 epigenetic mediators in uterine fibroids compared to myometrium using publicly available RNA sequencing (RNA-seq) data. To validate our findings, we performed RT-qPCR on a separate cohort of uterine fibroids targeting these modifiers confirming our RNA-seq data. We then examined protein profiles of key N6-methyladenosine (m6A) modifiers in fibroids and their matched myometrium, showing no significant differences in concordance with our RNA expression profiles. To determine RNA modification abundance, mRNA and small RNA from fibroids and matched myometrium were analyzed by ultra-high performance liquid chromatography-mass spectrometry identifying prevalent m6A and 11 other known modifiers. However, no aberrant expression in fibroids was detected. We then mined a previously published dataset and identified differential expression of m6A modifiers that were specific to fibroid genetic subtype. Our analysis also identified m6A consensus motifs on genes previously identified to be dysregulated in uterine fibroids. Overall, using state-of-the-art mass spectrometry, RNA expression, and protein profiles, we characterized and identified differentially expressed m6A modifiers in relation to driver mutations. Despite the use of several different approaches, we identified limited differential expression of RNA modifiers and associated modifications in uterine fibroids. However, considering the highly heterogenous genomic and cellular nature of fibroids, and the possible contribution of single molecule m6A modifications to fibroid pathology, there is a need for greater in-depth characterization of m6A marks and modifiers in a larger and diverse patient cohort.

Lupus IgA1 autoantibodies synergize with IgG to enhance plasmacytoid dendritic cell responses to RNA-containing immune complexes.

Autoantibodies to nuclear antigens are hallmarks of systemic lupus erythematosus (SLE) where they contribute to pathogenesis. However, there remains a gap in our knowledge regarding how different isotypes of autoantibodies contribute to this autoimmune disease, including the production of the critical type I interferon (IFN) cytokines by plasmacytoid dendritic cells (pDCs) in response to immune complexes (ICs). We focused on IgA, which is the second-most prevalent isotype in serum and, along with IgG, is deposited in glomeruli in individuals with lupus nephritis. We show that individuals with SLE have serum IgA autoantibodies against most nuclear antigens, correlating with IgG against the same antigen. We investigated whether IgA autoantibodies against a major SLE autoantigen, Smith ribonucleoprotein (Sm/RNP), played a role in IC activation of pDCs. We found that pDCs expressed the IgA-specific Fc receptor, FcαR, and IgA1 autoantibodies synergized with IgG in RNA-containing ICs to generate robust primary blood pDC IFN-α responses in vitro. pDC responses to these ICs required both FcαR and FcγRIIa, showing synergy between these Fc receptors. Sm/RNP IC binding to and internalization by pDCs were greater when ICs contained both IgA1 and IgG. Circulating pDCs from individuals with SLE had higher binding of IgA1-containing ICs and higher expression of FcαR than pDCs from healthy control individuals. Although pDC FcαR expression correlated with the blood IFN-stimulated gene signature in SLE, Toll-like receptor 7 agonists, but not IFN-α, up-regulated pDC FcαR expression in vitro. Together, we show a mechanism by which IgA1 autoantibodies contribute to SLE pathogenesis.

Thermodynamic coupling of the tandem RRM domains of hnRNP A1 underlie its pleiotropic RNA binding functions.

The functional properties of RNA binding proteins (RBPs) require allosteric regulation through interdomain communication. Despite the importance of allostery to biological regulation, only a few studies have been conducted to describe the biophysical nature by which interdomain communication manifests in RBPs. Here, we show for hnRNP A1 that interdomain communication is vital for the unique stability of its amino-terminal domain, which consists of two RNA recognition motifs (RRMs). These RRMs exhibit drastically different stability under pressure. RRM2 unfolds as an individual domain but remains stable when appended to RRM1. Variants that disrupt interdomain communication between the tandem RRMs show a significant decrease in stability. Carrying these mutations over to the full-length protein for in vivo experiments revealed that the mutations affected the ability of the disordered carboxyl-terminal domain to engage in protein-protein interactions and influenced the protein's RNA binding capacity. Collectively, this work reveals that thermodynamic coupling between the tandem RRMs of hnRNP A1 accounts for its allosteric regulatory functions.

TracrRNA reprogramming enables direct PAM-independent detection of RNA with diverse DNA-targeting Cas12 nucleases.

Many CRISPR-Cas immune systems generate guide (g)RNAs using trans-activating CRISPR RNAs (tracrRNAs). Recent work revealed that Cas9 tracrRNAs could be reprogrammed to convert any RNA-of-interest into a gRNA, linking the RNA's presence to Cas9-mediated cleavage of double-stranded (ds)DNA. Here, we reprogram tracrRNAs from diverse Cas12 nucleases, linking the presence of an RNA-of-interest to dsDNA cleavage and subsequent collateral single-stranded DNA cleavage-all without the RNA necessarily encoding a protospacer-adjacent motif (PAM). After elucidating nuclease-specific design rules, we demonstrate PAM-independent RNA detection with Cas12b, Cas12e, and Cas12f nucleases. Furthermore, rationally truncating the dsDNA target boosts collateral cleavage activity, while the absence of a gRNA reduces background collateral activity and enhances sensitivity. Finally, we apply this platform to detect 16 S rRNA sequences from five different bacterial pathogens using a universal reprogrammed tracrRNA. These findings extend tracrRNA reprogramming to diverse dsDNA-targeting Cas12 nucleases, expanding the flexibility and versatility of CRISPR-based RNA detection.

Self-supervised learning for characterising histomorphological diversity and spatial RNA expression prediction across 23 human tissue types.

As vast histological archives are digitised, there is a pressing need to be able to associate specific tissue substructures and incident pathology to disease outcomes without arduous annotation. Here, we learn self-supervised representations using a Vision Transformer, trained on 1.7 M histology images across 23 healthy tissues in 838 donors from the Genotype Tissue Expression consortium (GTEx). Using these representations, we can automatically segment tissues into their constituent tissue substructures and pathology proportions across thousands of whole slide images, outperforming other self-supervised methods (43% increase in silhouette score). Additionally, we can detect and quantify histological pathologies present, such as arterial calcification (AUROC = 0.93) and identify missing calcification diagnoses. Finally, to link gene expression to tissue morphology, we introduce RNAPath, a set of models trained on 23 tissue types that can predict and spatially localise individual RNA expression levels directly from H&E histology (mean genes significantly regressed = 5156, FDR 1%). We validate RNAPath spatial predictions with matched ground truth immunohistochemistry for several well characterised control genes, recapitulating their known spatial specificity. Together, these results demonstrate how self-supervised machine learning when applied to vast histological archives allows researchers to answer questions about tissue pathology, its spatial organisation and the interplay between morphological tissue variability and gene expression.

RNA Adduction Resulting from the Metabolic Activation of Myristicin by P450 Enzymes and Sulfotransferases.

Myristicin (MYR) mainly occurs in nutmeg and belongs to alkoxy-substituted allylbenzenes, a class of potentially toxic natural chemicals. RNA interaction with MYR metabolites in vitro and in vivo has been investigated in order to gain a better understanding of MYR toxicities. We detected two guanosine adducts (GA1 and GA2), two adenosine adducts (AA1 and AA2), and two cytosine adducts (CA1 and CA2) by LC-MS/MS analysis of total RNA extracts from cultured primary mouse hepatocytes and liver tissues of mice after exposure to MYR. An order of nucleoside adductions was found to be GAs > AAs > CAs, and the result of density functional theory calculations was in agreement with that detected by the LC-MS/MS-based approach. In vitro and in vivo studies have shown that MYR was oxidized by cytochrome P450 enzymes to 1'-hydroxyl and 3'-hydroxyl metabolites, which were then sulfated by sulfotransferases (SULTs) to form sulfate esters. The resulting sulfates would react with the nucleosides by SN1 and/or SN2 reactions, resulting in RNA adduction. The modification may alter the biochemical properties of RNA and disrupt RNA functions, perhaps partially contributing to the toxicities of MYR.

RNA scaffolds the Golgi ribbon by forming condensates with GM130.

The mammalian Golgi is composed of stacks that are laterally connected into a continuous ribbon-like structure. The integrity and function of the ribbon is disrupted under stress conditions, but the molecular mechanisms remain unclear. Here we show that the ribbon is maintained by biomolecular condensates of RNA and the Golgi matrix protein GM130 (GOLGA2). We identify GM130 as a membrane-bound RNA-binding protein, which directly recruits RNA and associated RNA-binding proteins to the Golgi membrane. Acute degradation of RNA or GM130 in cells disrupts the ribbon. Under stress conditions, RNA dissociates from GM130 and the ribbon is disjointed, but after the cells recover from stress the ribbon is restored. When overexpressed in cells, GM130 forms RNA-dependent liquid-like condensates. GM130 contains an intrinsically disordered domain at its amino terminus, which binds RNA to induce liquid-liquid phase separation. These co-condensates are sufficient to link purified Golgi membranes, reconstructing lateral linking of stacks into a ribbon-like structure. Together, these studies show that RNA acts as a structural biopolymer that together with GM130 maintains the integrity of the Golgi ribbon.

Analysis of culture and RNA isolation methods for precision-cut liver slices from cirrhotic rats.

Precision-cut liver slices (PCLS) are increasingly used as a model to investigate anti-fibrotic therapies. However, many studies use PCLS from healthy animals treated with pro-fibrotic stimuli in culture, which reflects only the early stages of fibrosis. The effects of different culture conditions on PCLS from cirrhotic animals has not been well characterized and there is no consensus on optimal methods. In this study, we report a method for the collection and culture of cirrhotic PCLS and compare the effect of common culture conditions on viability, function, and gene expression. Additionally, we compared three methods of RNA isolation and identified a protocol with high yield and purity. We observed significantly increased albumin production when cultured with insulin-transferrin-selenium and dexamethasone, and when incubated on a rocking platform. Culturing with insulin-transferrin-selenium and dexamethasone maintained gene expression closer to the levels in fresh slices. However, despite stable viability and function up to 4 days, we found significant changes in expression of key genes by day 2. Interestingly, we also observed that cirrhotic PCLS maintain viability in culture longer than slices from healthy animals. Due to the influence of matrix stiffness on fibrosis and hepatocellular function, it is important to evaluate prospective anti-fibrotic therapies in a platform that preserves tissue biomechanics. PCLS from cirrhotic animals represent a promising tool for the development of treatments for chronic liver disease.

Circular at the very beginning: on the initial genomes in the RNA world.

It is likely that an RNA world existed in early life, when RNA played both the roles of the genome and functional molecules, thereby undergoing Darwinian evolution. However, even with only one type of polymer, it seems quite necessary to introduce a labour division concerning these two roles because folding is required for functional molecules (ribozymes) but unfavourable for the genome (as a template in replication). Notably, while ribozymes tend to have adopted a linear form for folding without constraints, a circular form, which might have been topologically hindered in folding, seems more suitable for an RNA template. Another advantage of involving a circular genome could have been to resist RNA's end-degradation. Here, we explore the scenario of a circular RNA genome plus linear ribozyme(s) at the precellular stage of the RNA world through computer modelling. The results suggest that a one-gene scene could have been 'maintained', albeit with rather a low efficiency for the circular genome to produce the ribozyme, which required precise chain-break or chain-synthesis. This strict requirement may have been relieved by introducing a 'noncoding' sequence into the genome, which had the potential to derive a second gene through mutation. A two-gene scene may have 'run well' with the two corresponding ribozymes promoting the replication of the circular genome from different respects. Circular genomes with more genes might have arisen later in RNA-based protocells. Therefore, circular genomes, which are common in the modern living world, may have had their 'root' at the very beginning of life.

Identifying small-molecules binding sites in RNA conformational ensembles with SHAMAN.

The rational targeting of RNA with small molecules is hampered by our still limited understanding of RNA structural and dynamic properties. Most in silico tools for binding site identification rely on static structures and therefore cannot face the challenges posed by the dynamic nature of RNA molecules. Here, we present SHAMAN, a computational technique to identify potential small-molecule binding sites in RNA structural ensembles. SHAMAN enables exploring the conformational landscape of RNA with atomistic molecular dynamics simulations and at the same time identifying RNA pockets in an efficient way with the aid of probes and enhanced-sampling techniques. In our benchmark composed of large, structured riboswitches as well as small, flexible viral RNAs, SHAMAN successfully identifies all the experimentally resolved pockets and ranks them among the most favorite probe hotspots. Overall, SHAMAN sets a solid foundation for future drug design efforts targeting RNA with small molecules, effectively addressing the long-standing challenges in the field.

RNA 2'-O-methylation promotes persistent R-loop formation and AID-mediated IgH class switch recombination.

BACKGROUND: RNA-DNA hybrids or R-loops are associated with deleterious genomic instability and protective immunoglobulin class switch recombination (CSR). However, the underlying phenomenon regulating the two contrasting functions of R-loops is unknown. Notably, the underlying mechanism that protects R-loops from classic RNase H-mediated digestion thereby promoting persistence of CSR-associated R-loops during CSR remains elusive. RESULTS: Here, we report that during CSR, R-loops formed at the immunoglobulin heavy (IgH) chain are modified by ribose 2'-O-methylation (2'-OMe). Moreover, we find that 2'-O-methyltransferase fibrillarin (FBL) interacts with activation-induced cytidine deaminase (AID) associated snoRNA aSNORD1C to facilitate the 2'-OMe. Moreover, deleting AID C-terminal tail impairs its association with aSNORD1C and FBL. Disrupting FBL, AID or aSNORD1C expression severely impairs 2'-OMe, R-loop stability and CSR. Surprisingly, FBL, AID's interaction partner and aSNORD1C promoted AID targeting to the IgH locus. CONCLUSION: Taken together, our results suggest that 2'-OMe stabilizes IgH-associated R-loops to enable productive CSR. These results would shed light on AID-mediated CSR and explain the mechanism of R-loop-associated genomic instability.

Exploring functional conservation in silico: a new machine learning approach to RNA-editing.

Around 50 years ago, molecular biology opened the path to understand changes in forms, adaptations, complexity, or the basis of human diseases through myriads of reports on gene birth, gene duplication, gene expression regulation, and splicing regulation, among other relevant mechanisms behind gene function. Here, with the advent of big data and artificial intelligence (AI), we focus on an elusive and intriguing mechanism of gene function regulation, RNA editing, in which a single nucleotide from an RNA molecule is changed, with a remarkable impact in the increase of the complexity of the transcriptome and proteome. We present a new generation approach to assess the functional conservation of the RNA-editing targeting mechanism using two AI learning algorithms, random forest (RF) and bidirectional long short-term memory (biLSTM) neural networks with an attention layer. These algorithms, combined with RNA-editing data coming from databases and variant calling from same-individual RNA and DNA-seq experiments from different species, allowed us to predict RNA-editing events using both primary sequence and secondary structure. Then, we devised a method for assessing conservation or divergence in the molecular mechanisms of editing completely in silico: the cross-testing analysis. This novel method not only helps to understand the conservation of the editing mechanism through evolution but could set the basis for achieving a better understanding of the adenosine-targeting mechanism in other fields.