Synthetic circular RNA switches and circuits that control protein expression in mammalian cells.

Synthetic messenger RNA (mRNA) has been focused on as an emerging application for mRNA-based therapies and vaccinations. Recently, synthetic circular RNAs (circRNAs) have shown promise as a new class of synthetic mRNA that enables superior stability and persistent gene expression in cells. However, translational control of circRNA remained challenging. Here, we develop 'circRNA switches' capable of controlling protein expression from circRNA by sensing intracellular RNA or proteins. We designed microRNA (miRNA) and protein-responsive circRNA switches by inserting miRNA-binding or protein-binding sequences into untranslated regions (UTRs), or Coxsackievirus B3 Internal Ribosome Entry Site (CVB3 IRES), respectively. Engineered circRNAs efficiently expressed reporter proteins without inducing severe cell cytotoxicity and immunogenicity, and responded to target miRNAs or proteins, controlling translation levels from circRNA in a cell type-specific manner. Moreover, we constructed circRNA-based gene circuits that selectively activated translation by detecting endogenous miRNA, by connecting miRNA and protein-responsive circRNAs. The designed circRNA circuits performed better than the linear mRNA-based circuits in terms of persistent expression levels. Synthetic circRNA devices provide new insights into RNA engineering and have a potential for RNA synthetic biology and therapies.

3dRNA: 3D Structure Prediction from Linear to Circular RNAs.

3D structures of RNAs are the basis for understanding their biological functions. However, experimentally solved RNA 3D structures are very limited. Therefore, many computational methods have been proposed to solve this problem, including our 3dRNA. 3dRNA is an automated template-based method of building RNA 3D structures from sequences and secondary structures by using the smallest secondary elements (SSEs) (http://biophy.hust.edu.cn/new/3dRNA). The first version of 3dRNA simply predicts an assembled structure for a target RNA. Later, it is improved to generate a set of assembled models and a method to further optimize them using experimental or theoretical restraints. In particular, pseudoknot base pairings are treated as restraints to solve the problem of no 3D templates for pseudoknots. Here 3dRNA is further extended to predict the 3D structures of circular RNAs since thousands of circular RNAs have been found recently but no 3D structures of them have been determined up to now. We show that circular RNAs can be divided into four types and two types show similar 3D structures with their linear counterparts while two types very different. We also show that the predicted structures of circular RNAs can bind to their ligands more stable than those of their linear counterparts, consistent with experimental results.

CRBPDL: Identification of circRNA-RBP interaction sites using an ensemble neural network approach.

Circular RNAs (circRNAs) are non-coding RNAs with a special circular structure produced formed by the reverse splicing mechanism. Increasing evidence shows that circular RNAs can directly bind to RNA-binding proteins (RBP) and play an important role in a variety of biological activities. The interactions between circRNAs and RBPs are key to comprehending the mechanism of posttranscriptional regulation. Accurately identifying binding sites is very useful for analyzing interactions. In past research, some predictors on the basis of machine learning (ML) have been presented, but prediction accuracy still needs to be ameliorated. Therefore, we present a novel calculation model, CRBPDL, which uses an Adaboost integrated deep hierarchical network to identify the binding sites of circular RNA-RBP. CRBPDL combines five different feature encoding schemes to encode the original RNA sequence, uses deep multiscale residual networks (MSRN) and bidirectional gating recurrent units (BiGRUs) to effectively learn high-level feature representations, it is sufficient to extract local and global context information at the same time. Additionally, a self-attention mechanism is employed to train the robustness of the CRBPDL. Ultimately, the Adaboost algorithm is applied to integrate deep learning (DL) model to improve prediction performance and reliability of the model. To verify the usefulness of CRBPDL, we compared the efficiency with state-of-the-art methods on 37 circular RNA data sets and 31 linear RNA data sets. Moreover, results display that CRBPDL is capable of performing universal, reliable, and robust. The code and data sets are obtainable at https://github.com/nmt315320/CRBPDL.git.

ViroidDB: a database of viroids and viroid-like circular RNAs.

We introduce ViroidDB, a value-added database that attempts to collect all known viroid and viroid-like circular RNA sequences into a single resource. Spanning about 10 000 unique sequences, ViroidDB includes viroids, retroviroid-like elements, small circular satellite RNAs, ribozyviruses, and retrozymes. Each sequence's secondary structure, ribozyme content, and cluster membership are predicted via a custom pipeline optimized for handling circular RNAs. The data can be explored via a purpose-built user interface that features visualizations, multiple sequence alignments, and a portal for downloading bulk data. Users can browse the data by sequence type, taxon, or typo-tolerant search of metadata fields. The database is freely accessible at https://viroids.org.

Hepatitis Delta Virus Genome RNA Synthesis Initiates at Position 1646 with a Nontemplated Guanosine.

Hepatitis delta virus (HDV) is a significant human pathogen that causes acute and chronic liver disease; there is no licensed therapy. HDV is a circular negative-sense single-stranded RNA (ssRNA) virus that produces three RNAs in infected cells, genome, antigenome, and mRNA; the latter encodes hepatitis delta antigen (HDAg), the viral protein. These RNAs are synthesized by host DNA-dependent RNA polymerase acting as an RNA-dependent RNA polymerase. Although HDV genome RNA accumulates to high levels in infected cells, the mechanism by which this process occurs remains poorly understood. For example, the nature of the 5' end of the genome, including the synthesis start site and its chemical composition, is not known. Analysis of this process has been challenging because the initiation site is part of an unstable precursor in the rolling-circle mechanism by which HDV genome RNA is synthesized. In this study, circular HDV antigenome RNAs synthesized in vitro were used to directly initiate HDV genome RNA synthesis in transfected cells, thus enabling the detection of the 5' end of the genome RNA. The 5' end of this RNA is capped, as expected for a polymerase II product. Initiation begins at position 1646 on the genome, which is located near the loop end proximal to the start site for HDAg mRNA synthesis. Unexpectedly, synthesis begins with a guanosine that is not conventionally templated by the HDV RNA. IMPORTANCE Hepatitis delta virus (HDV) is a unique virus that causes severe liver disease. It uses host RNA polymerase II to copy its circular RNA genome in a unique and poorly understood process. Although the virus RNA accumulates to high levels within infected cells, it is not known how the synthesis of the viral RNA begins or even where on the genome synthesis starts. Here, we identify the start site for the initiation of HDV genome RNA synthesis as position 1646, which is at one end of the closed-hairpin-like structure of the viral RNA. The 5' end of the RNA is capped, as expected for polymerase II products. However, RNA synthesis begins with a guanosine that is not present in the genome. Thus, although HDV uses polymerase II to synthesize the viral genome, some details of the initiation process are different. These differences could be important for successfully targeting virus replication.

circRNA N6-methyladenosine methylation in preeclampsia and the potential role of N6-methyladenosine-modified circPAPPA2 in trophoblast invasion.

Here, we performed N6-methyladenosine (m6A) RNA sequencing to determine the circRNA m6A methylation changes in the placentas during the pathogenesis of preeclampsia (PE). We verified the expression of the circRNA circPAPPA2 using quantitative reverse transcription-PCR. An invasion assay was carried out to identify the role of circPAPPA2 in the development of PE. Mechanistically, we investigated the cause of the altered m6A modification of circPAPPA2 through overexpression and knockdown cell experiments, RNA immunoprecipitation, fluorescence in situ hybridization and RNA stability experiments. We found that increases in m6A-modified circRNAs are prevalent in PE placentas and that the main changes in methylation occur in the 3'UTR and near the start codon, implicating the involvement of these changes in PE development. We also found that the levels of circPAPPA2 are decreased but that m6A modification is augmented. Furthermore, we discovered that methyltransferase­like 14 (METTL14) increases the level of circPAPPA2 m6A methylation and that insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) maintains circPAPPA2 stability. Decreases in IGF2BP3 levels lead to declines in circPAPPA2 levels. In summary, we provide a new vision and strategy for the study of PE pathology and report that placental circRNA m6A modification appears to be an important regulatory mechanism.

Circular versus linear RNA topology: different modes of RNA-RNA interactions in vitro and in human cells.

Circular RNA is progressively reported to occur in various species including mammals where it is thought to be involved in the post-transcriptional regulation of gene expression, partly via interactions with microRNA. Here, we asked whether the circular topology causes functional differences to linear forms when interacting with short RNA strands in vitro and in human cells. Kinetic studies with human bladder cancer-derived synthetic circular RNA versus linear transcripts, respectively, with short oligoribonucleotides showed similar association rates for both topologies. Conversely, a substantial topology-related difference was measured for the activation entropy and the activation enthalpy of RNA-RNA annealing. This finding strongly indicates a significant difference of the mechanism of RNA-RNA interactions. To investigate whether these characteristics of circular RNA are biologically meaningful we performed transient transfection experiments with a microRNA-regulated expression system for luciferase in bladder cancer-derived cells. We co-transfected linear or circular RNA containing one microRNA binding site for the target-suppressing microRNA mlet7a. Here, the circular isoform showed a strongly increased competition with microRNA function versus linear versions. In summary, this study suggests novel topology-related characteristics of RNA-RNA interactions involving circRNA in vitro and in living cells.

circFL-seq reveals full-length circular RNAs with rolling circular reverse transcription and nanopore sequencing.

Circular RNAs (circRNAs) act through multiple mechanisms via their sequence features to fine-tune gene expression networks. Due to overlapping sequences with linear cognates, identifying internal sequences of circRNAs remains a challenge, which hinders a comprehensive understanding of circRNA functions and mechanisms. Here, based on rolling circular reverse transcription and nanopore sequencing, we developed circFL-seq, a full-length circRNA sequencing method, to profile circRNA at the isoform level. With a customized computational pipeline to directly identify full-length sequences from rolling circular reads, we reconstructed 77,606 high-quality circRNAs from seven human cell lines and two human tissues. circFL-seq benefits from rolling circles and long-read sequencing, and the results showed more than tenfold enrichment of circRNA reads and advantages for both detection and quantification at the isoform level compared to those for short-read RNA sequencing. The concordance of the RT-qPCR and circFL-seq results for the identification of differential alternative splicing suggested wide application prospects for functional studies of internal variants in circRNAs. Moreover, the detection of fusion circRNAs at the omics scale may further expand the application of circFL-seq. Taken together, the accurate identification and quantification of full-length circRNAs make circFL-seq a potential tool for large-scale screening of functional circRNAs.

Prediction of RBP binding sites on circRNAs using an LSTM-based deep sequence learning architecture.

Circular RNAs (circRNAs) are widely expressed in highly diverged eukaryotes. Although circRNAs have been known for many years, their function remains unclear. Interaction with RNA-binding protein (RBP) to influence post-transcriptional regulation is considered to be an important pathway for circRNA function, such as acting as an oncogenic RBP sponge to inhibit cancer. In this study, we design a deep learning framework, CRPBsites, to predict the binding sites of RBPs on circRNAs. In this model, the sequences of variable-length binding sites are transformed into embedding vectors by word2vec model. Bidirectional LSTM is used to encode the embedding vectors of binding sites, and then they are fed into another LSTM decoder for decoding and classification tasks. To train and test the model, we construct four datasets that contain sequences of variable-length binding sites on circRNAs, and each set corresponds to an RBP, which is overexpressed in bladder cancer tissues. Experimental results on four datasets and comparison with other existing models show that CRPBsites has superior performance. Afterwards, we found that there were highly similar binding motifs in the four binding site datasets. Finally, we applied well-trained CRPBsites to identify the binding sites of IGF2BP1 on circCDYL, and the results proved the effectiveness of this method. In conclusion, CRPBsites is an effective prediction model for circRNA-RBP interaction site identification. We hope that CRPBsites can provide valuable guidance for experimental studies on the influence of circRNA on post-transcriptional regulation.

The power and the promise of circRNAs for cancer precision medicine with functional diagnostics and prognostic prediction.

Circular RNA (circRNA) is a large class of covalently closed circRNA. As a member of competitive endogenous RNA, it participates in the regulation of circRNA-miRNA-mRNA network and plays an important role in the regulation of physiology and pathology. CircRNA is produced by the reverse splicing of exon, intron or both, forming exon or intron circRNA. Studies have shown that circRNA is a ubiquitous molecule, which exceeds the linear mRNA distributed in human cells. Because of its covalent closed-loop structure, circRNA is resistant to RNase R, which is more stable than linear mRNA; circRNA is highly conserved in different species. It was found that circRNA competitively adsorbs miRNA, as a miRNA sponge, to involve in the expression regulation of a variety of genes and plays an important role in tumor development, invasion, metastasis and other processes. These molecules offer new potential opportunities for therapeutic intervention and serve as biomarkers for diagnosis. In this paper, the origin, characteristics and functions of circRNA and its role in tumor development, invasion and metastasis, diagnosis and prognosis are reviewed.

Micro-Raman Characterization of Structural Features of High-k Stack Layer of SOI Nanowire Chip, Designed to Detect Circular RNA Associated with the Development of Glioma.

The application of micro-Raman spectroscopy was used for characterization of structural features of the high-k stack (h-k) layer of "silicon-on-insulator" (SOI) nanowire (NW) chip (h-k-SOI-NW chip), including Al2O3 and HfO2 in various combinations after heat treatment from 425 to 1000 °C. After that, the NW structures h-k-SOI-NW chip was created using gas plasma etching optical lithography. The stability of the signals from the monocrine phase of HfO2 was shown. Significant differences were found in the elastic stresses of the silicon layers for very thick (>200 nm) Al2O3 layers. In the UV spectra of SOI layers of a silicon substrate with HfO2, shoulders in the Raman spectrum were observed at 480-490 cm-1 of single-phonon scattering. The h-k-SOI-NW chip created in this way has been used for the detection of DNA-oligonucleotide sequences (oDNA), that became a synthetic analog of circular RNA-circ-SHKBP1 associated with the development of glioma at a concentration of 1.1 × 10-16 M. The possibility of using such h-k-SOI NW chips for the detection of circ-SHKBP1 in blood plasma of patients diagnosed with neoplasm of uncertain nature of the brain and central nervous system was shown.

Circular L-RNA aptamer promotes target recognition and controls gene activity.

Rational design of aptamers to incorporate unnatural nucleotides and special chemical moieties can expand their functional complexity and diversity. Spiegelmer (L-RNA aptamer) is a unique class of aptamer that is composed of unnatural L-RNA nucleotides, and so far there are limited L-RNA aptamer candidates and applications being reported. Moreover, the target binding properties of current L-RNA aptamers require significant improvement. Here, using L-Apt.4-1c as an example, we develop a simple and robust strategy to generate the first circular L-RNA aptamer, cycL-Apt.4-1c, quantitatively, demonstrate substantial enhancement in binding affinity and selectivity toward its target, and notably report novel applications of circular L-RNA aptamer in controlling RNA-protein interaction, and gene activity including telomerase activity and gene expression. Our approach and findings will be applicable to any L-RNA aptamers and open up a new avenue for diverse applications.

Circ_0025908 regulates cell vitality and proliferation via miR-137/HIPK2 axis of rheumatic arthritis.

BACKGROUND: Rheumatic arthritis (RA) is an autoimmune disease with bad effects. Recent researches have shown that circular RNAs (circRNAs) could affect the progress of RA, but the mechanism still indistinct. In this work, we explored the roles of circ_0025908 in RA. METHODS: The levels of circ_0025908, microRNA-137 (miR-137), and mRNA of homeodomain-interacting protein kinase 2 (HIPK2) were detected by quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) in RA tissues. Meanwhile, the level of HIPK2 was quantified by Western blot analysis. Besides, the cell functions were examined by CCK8 assay, EdU assay, flow cytometry assay, ELISA, and Western blot. Furthermore, the interplay between miR-137 and circ_0025908 or HIPK2 was detected by dual-luciferase reporter assay. RESULTS: The levels of circ_0025908 and HIPK2 were upregulated, and the miR-137 level was decreased in RA tissues in contrast to that in normal tissues. For functional analysis, circ_0025908 deficiency inhibited cell vitality, cell mitotic cycle, cell proliferation, and immunoreaction in RA cells, whereas promoted cell apoptosis. Moreover, miR-137 was confirmed to repress the progression of RA cells by suppressing HIPK2. In mechanism, circ_0025908 acted as a miR-137 sponge to regulate the level of HIPK2. CONCLUSION: Circ_0025908 facilitates the development of RA through increasing HIPK2 expression by regulating miR-137, which also offered an underlying targeted therapy for RA treatment.

catRAPID omics v2.0: going deeper and wider in the prediction of protein-RNA interactions.

Prediction of protein-RNA interactions is important to understand post-transcriptional events taking place in the cell. Here we introduce catRAPID omics v2.0, an update of our web server dedicated to the computation of protein-RNA interaction propensities at the transcriptome- and RNA-binding proteome-level in 8 model organisms. The server accepts multiple input protein or RNA sequences and computes their catRAPID interaction scores on updated precompiled libraries. Additionally, it is now possible to predict the interactions between a custom protein set and a custom RNA set. Considerable effort has been put into the generation of a new database of RNA-binding motifs that are searched within the predicted RNA targets of proteins. In this update, the sequence fragmentation scheme of the catRAPID fragment module has been included, which allows the server to handle long linear RNAs and to analyse circular RNAs. For the top-scoring protein-RNA pairs, the web server shows the predicted binding sites in both protein and RNA sequences and reports whether the predicted interactions are conserved in orthologous protein-RNA pairs. The catRAPID omics v2.0 web server is a powerful tool for the characterization and classification of RNA-protein interactions and is freely available at http://service.tartaglialab.com/page/catrapid_omics2_group along with documentation and tutorial.

NOVA2 regulates neural circRNA biogenesis.

Circular RNAs (circRNAs) are highly expressed in the brain and their expression increases during neuronal differentiation. The factors regulating circRNAs in the developing mouse brain are unknown. NOVA1 and NOVA2 are neural-enriched RNA-binding proteins with well-characterized roles in alternative splicing. Profiling of circRNAs from RNA-seq data revealed that global circRNA levels were reduced in embryonic cortex of Nova2 but not Nova1 knockout mice. Analysis of isolated inhibitory and excitatory cortical neurons lacking NOVA2 revealed an even more dramatic reduction of circRNAs and establishes a widespread role for NOVA2 in enhancing circRNA biogenesis. To investigate the cis-elements controlling NOVA2-regulation of circRNA biogenesis, we generated a backsplicing reporter based on the Efnb2 gene. We found that NOVA2-mediated backsplicing of circEfnb2 was impaired when YCAY clusters located in flanking introns were mutagenized. CLIP (cross-linking and immunoprecipitation) and additional reporter analyses demonstrated the importance of NOVA2 binding sites located in both flanking introns of circRNA loci. NOVA2 is the first RNA-binding protein identified to globally promote circRNA biogenesis in the developing brain.

Identification of over 200-fold more hairpin ribozymes than previously known in diverse circular RNAs.

Self-cleaving ribozymes are catalytic RNAs that cut themselves at a specific inter-nucleotide linkage. They serve as a model of RNA catalysis, and as an important tool in biotechnology. For most of the nine known structural classes of self-cleaving ribozymes, at least hundreds of examples are known, and some are present in multiple domains of life. By contrast, only four unique examples of the hairpin ribozyme class are known, despite its discovery in 1986. We bioinformatically predicted 941 unique hairpin ribozymes of a different permuted form from the four previously known hairpin ribozymes, and experimentally confirmed several diverse predictions. These results profoundly expand the number of natural hairpin ribozymes, enabling biochemical analysis based on natural sequences, and suggest that a distinct permuted form is more biologically relevant. Moreover, all novel hairpins were discovered in metatranscriptomes. They apparently reside in RNA molecules that vary both in size-from 381 to 5170 nucleotides-and in protein content. The RNA molecules likely replicate as circular single-stranded RNAs, and potentially provide a dramatic increase in diversity of such RNAs. Moreover, these organisms have eluded previous attempts to isolate RNA viruses from metatranscriptomes-suggesting a significant untapped universe of viruses or other organisms hidden within metatranscriptome sequences.

Computational Analysis of circRNA Expression Data.

Analysis of circular RNA (circRNA) expression from RNA-Seq data can be performed with different algorithms and analysis pipelines, tools allowing the extraction of heterogeneous information on the expression of this novel class of RNAs. Computational pipelines were developed to facilitate the analysis of circRNA expression by leveraging different public tools in easy-to-use pipelines. This chapter describes the complete workflow for a computationally reproducible analysis of circRNA expression starting for a public RNA-Seq experiment. The main steps of circRNA prediction, annotation, classification, sequence reconstruction, quantification, and differential expression are illustrated.

Peripheral blood hsa-circRNA5333-4: A novel biomarker for myasthenia gravis.

In this study, the potential of specific Circular RNAs (circRNAs) as novel peripheral blood biomarkers for myasthenia gravis (MG) was explored. We analyzed circRNAs in the peripheral blood of three normal controls and three MG patients using RNA microarray. Candidate circRNAs were validated in three independent cohorts by Quantitative Real-time polymerase chain reaction (qPCR). Eleven differentially expressed circRNAs were initially identified and four were confirmed in the first independent cohort. Hsa_circ_0076490 and hsa-circ_5333-4 had the largest areas under the curve (AUCs) of the receiver operating characteristics (ROC) and were validated in the second cohort. In the third cohort, hsa-circRNA5333-4 had a larger AUC: 0.864 (95% confidence interval [CI] = 0.801-0.928, P < 0.001), a stronger correlation with the Quantitative Myasthenia Gravis Score (qMG): r = 0.505 (P < 0.001) and was correlated with gender and acetylcholine receptor antibody levels (P < 0.05). So hsa-circRNA5333-4 represents a novel biomarker for the diagnosis and monitoring of MG.

Characterizing and circumventing sequence restrictions for synthesis of circular RNA in vitro.

Just as eukaryotic circular RNA (circRNA) is a product of intracellular backsplicing, custom circRNA can be synthesized in vitro using a transcription template in which transposed halves of a split group I intron flank the sequence of the RNA to be circularized. Such permuted intron-exon (PIE) constructs have been used to produce circRNA versions of ribozymes, mimics of viral RNA motifs, a streptavidin aptamer, and protein expression vectors for genetic engineering and vaccine development. One limitation of this approach is the obligatory incorporation of small RNA segments (E1 and E2) into nascent circRNA at the site of end-joining. This restriction may preclude synthesis of small circRNA therapeutics and RNA nanoparticles that are sensitive to extraneous sequence, as well as larger circRNA mimics whose sequences must precisely match those of the native species on which they are modelled. In this work, we used serial mutagenesis and in vitro selection to determine how varying E1 and E2 sequences in a thymidylate synthase (td) group I intron PIE transcription template construct affects circRNA synthesis yield. Based on our collective findings, we present guidelines for the design of custom-tailored PIE transcription templates from which synthetic circRNAs of almost any sequence may be efficiently synthesized.

Dengue virus strain 2 capsid protein switches the annealing pathway and reduces intrinsic dynamics of the conserved 5' untranslated region.

The capsid protein of dengue virus strain 2 (DENV2C) promotes nucleic acid structural rearrangements using chaperone activity. However, the role of DENV2C during the interaction of RNA elements in the conserved 5' untranslated region (5'UTR) to the 3' untranslated region (3'UTR) is still unclear. Thus, we investigated the effect of DENV2C on the annealing mechanism of two RNA hairpin elements from the 5'UTR to their complementary sequences during (+)/(-) ds-RNAformation and (+) RNA circularization. DENV2C was found to switch the annealing pathway for RNA elements involved in (+)/(-) ds-RNA formation, but not for RNA elements related to (+) RNA circularization. In addition, we also determined that DENV2C modulates intrinsic dynamics and reduces kinetically trapped unfavourable conformations of the 5'UTR sequence. Thus, our results provide mechanistic insights by which DENV2C chaperones the interactions between RNA elements at the 5' and 3' ends during genome recombination, a prerequisite for DENV replication.