RNA Regulatory Networks 2.0.

The central role of RNA molecules in cell biology has been an expanding subject of study since the proposal of the "RNA world" hypothesis 60 years ago [...].

RPflex: A Coarse-Grained Network Model for RNA Pocket Flexibility Study.

RNA regulates various biological processes, such as gene regulation, RNA splicing, and intracellular signal transduction. RNA's conformational dynamics play crucial roles in performing its diverse functions. Thus, it is essential to explore the flexibility characteristics of RNA, especially pocket flexibility. Here, we propose a computational approach, RPflex, to analyze pocket flexibility using the coarse-grained network model. We first clustered 3154 pockets into 297 groups by similarity calculation based on the coarse-grained lattice model. Then, we introduced the flexibility score to quantify the flexibility by global pocket features. The results show strong correlations between the flexibility scores and root-mean-square fluctuation (RMSF) values, with Pearson correlation coefficients of 0.60, 0.76, and 0.53 in Testing Sets I-III. Considering both flexibility score and network calculations, the Pearson correlation coefficient was increased to 0.71 in flexible pockets on Testing Set IV. The network calculations reveal that the long-range interaction changes contributed most to flexibility. In addition, the hydrogen bonds in the base-base interactions greatly stabilize the RNA structure, while backbone interactions determine RNA folding. The computational analysis of pocket flexibility could facilitate RNA engineering for biological or medical applications.

Self-Amplifying RNA Approach for Protein Replacement Therapy.

Messenger RNA (mRNA) technology has already been successfully tested preclinically and there are ongoing clinical trials for protein replacement purposes; however, more effort has been put into the development of prevention strategies against infectious diseases. Apparently, mRNA vaccine approval against coronavirus disease 2019 (COVID-19) is a landmark for opening new opportunities for managing diverse health disorders based on this approach. Indeed, apart from infectious diseases, it has also been widely tested in numerous directions including cancer prevention and the treatment of inherited disorders. Interestingly, self-amplifying RNA (saRNA)-based technology is believed to display more developed RNA therapy compared with conventional mRNA technique in terms of its lower dosage requirements, relatively fewer side effects, and possessing long-lasting effects. Nevertheless, some challenges still exist that need to be overcome in order to achieve saRNA-based drug approval in clinics. Hence, the current review discusses the feasibility of saRNA utility for protein replacement therapy on various health disorders including rare hereditary diseases and also provides a detailed overview of saRNA advantages, its molecular structure, mechanism of action, and relevant delivery platforms.

Knotify+: Toward the Prediction of RNA H-Type Pseudoknots, Including Bulges and Internal Loops.

The accurate "base pairing" in RNA molecules, which leads to the prediction of RNA secondary structures, is crucial in order to explain unknown biological operations. Recently, COVID-19, a widespread disease, has caused many deaths, affecting humanity in an unprecedented way. SARS-CoV-2, a single-stranded RNA virus, has shown the significance of analyzing these molecules and their structures. This paper aims to create a pioneering framework in the direction of predicting specific RNA structures, leveraging syntactic pattern recognition. The proposed framework, Knotify+, addresses the problem of predicting H-type pseudoknots, including bulges and internal loops, by featuring the power of context-free grammar (CFG). We combine the grammar's advantages with maximum base pairing and minimum free energy to tackle this ambiguous task in a performant way. Specifically, our proposed methodology, Knotify+, outperforms state-of-the-art frameworks with regards to its accuracy in core stems prediction. Additionally, it performs more accurately in small sequences and presents a comparable accuracy rate in larger ones, while it requires a smaller execution time compared to well-known platforms. The Knotify+ source code and implementation details are available as a public repository on GitHub.

Effects of Epitranscriptomic RNA Modifications on the Catalytic Activity of the SARS-CoV-2 Replication Complex.

SARS-CoV-2 causes individualized symptoms. Many reasons have been given. We propose that an individual's epitranscriptomic system could be responsible as well. The viral RNA genome can be subject to epitranscriptomic modifications, which can be different for different individuals, and thus epitranscriptomics can affect many events including RNA replication differently. In this context, we studied the effects of modifications including pseudouridine (Ψ), 5-methylcytosine (m5 C), N6-methyladenosine (m6 A), N1-methyladenosine (m1 A) and N3-methylcytosine (m3 C) on the activity of SARS-CoV-2 replication complex (SC2RC). We found that Ψ, m5 C, m6 A and m3 C had little effect, whereas m1 A inhibited the enzyme. Both m1 A and m3 C disrupt canonical base pairing, but they had different effects. The fact that m1 A inhibits SC2RC implies that the modification can be difficult to detect. This fact also implies that individuals with upregulated m1 A including cancer, obesity and diabetes patients might have milder symptoms. However, this contradicts clinical observations. Relevant discussions are provided.

Circular RNA cancer vaccines drive immunity in hard-to-treat malignancies.

Rationale: Messenger RNA (mRNA) vaccine outperforms other kinds of cancer immunotherapy due to its high response rates, easy preparation, and wide applicability, which is considered as one of the most promising forms of next-generation cancer therapies. However, the inherent instability and insufficient protein expression duration of mRNA limit the efficacy and widespread application of the vaccine. Methods: Here, we first tested the possibility of a novel circular RNA (circRNA) platform for protein expression and compare its duration with linear RNA. Then, we developed a lipid nanoparticle (LNP) system for circRNA delivery in vitro and in vivo. Next, the innate and adaptive immune response of circRNA-LNP complex was evaluated in vivo. The anti-tumor efficacy of circRNA-LNP was further confirmed in three tumor models. Finally, the possibility of combination therapy with circRNA-LNP and adoptive cell transfer therapy was further investigated in a late-stage tumor model. Results: We successfully increased the stability of the RNA vaccine by circularizing the linear RNA molecules to form highly stable circRNA molecules which exhibited durable protein expression ability. By encapsulating the antigen-coding circRNA in LNP enabling in vivo expression, we established a novel circRNA vaccine platform, which was capable of triggering robust innate and adaptive immune activation and showed superior anti-tumor efficacy in multiple mouse tumor models. Conclusions: Overall, our circRNA vaccine platform provides a novel prospect for the development of cancer RNA vaccines in a wide range of hard-to-treat malignancies.

Single-cell RNA-sequencing in asthma research.

Asthma is a complex and heterogeneous disease with multicellular involvement, and knowledge gaps remain in our understanding of the pathogenesis of asthma. Efforts are still being made to investigate the immune pathogenesis of asthma in order to identify possible targets for prevention. Single cell RNA sequencing (scRNA-seq) technology is a useful tool for exploring heterogeneous diseases, identifying rare cell types and distinct cell subsets, enabling elucidation of key processes of cell differentiation, and understanding regulatory gene networks that predict immune function. In this article, we provide an overview of the importance of scRNA-seq for asthma research, followed by an in-depth discussion of the results in recent years, in order to provide new ideas for the pathogenesis, drug development and treatment of asthma.

Circular RNA: An emerging frontier in RNA therapeutic targets, RNA therapeutics, and mRNA vaccines.

Circular RNAs (circRNA) is a class of natural (biogenic) or synthetic closed RNA without 5' or 3' ends. Meanwhile, their unique covalently-closed structures of circRNA prevent RNA degradation by exonucleases, thereby empowering them with high pharmaceutical stability and biostability relative to current standard-of-care linear mRNA. Natural circRNA can be non-coding RNAs as well as protein-coding RNA, the latter of which was recently discovered. The physiological functions of biogenic circRNAs, which largely remain elusive, include protein and gene sponges, cell activity modulators, and protein translation. The discovery that the circRNA levels can be correlated with some human diseases empowers circRNA with the potential as a novel type of disease biomarkers and a noncanonical class of therapeutic targets. Recently, synthetic circRNA have been engineered to explore their applications as a novel class of mRNA therapeutics and vaccines. In this review, we will discuss the current understanding of the biogenesis and physiological functions of natural circRNAs, the approaches to circRNA synthesis, and current research in the exploration of endogenous circRNAs as novel therapeutic targets and testing circRNAs as an emerging class of RNA therapeutics and vaccines.

Construction and evaluation of a self-replicative RNA vaccine against SARS-CoV-2 using yellow fever virus replicon.

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a global threat. To forestall the pandemic, developing safe and effective vaccines is necessary. Because of the rapid production and little effect on the host genome, mRNA vaccines are attractive, but they have a relatively low immune response after a single dose. Replicon RNA (repRNA) is a promising vaccine platform for safety and efficacy. RepRNA vaccine encodes not only antigen genes but also the genes necessary for RNA replication. Thus, repRNA is self-replicative and can play the role of an adjuvant by itself, which elicits robust immunity. This study constructed and evaluated a repRNA vaccine in which the gene encoding the spike (S) protein of SARS-CoV-2 was inserted into a replicon of yellow fever virus 17D strain. Upon electroporation of this repRNA into baby hamster kidney cells, the S protein and yellow fever virus protein were co-expressed. Additionally, the self-replication ability of repRNA vaccine was confirmed using qRT-PCR, demonstrating its potency as a vaccine. Immunization of C57BL/6 mice with 1 µg of the repRNA vaccine induced specific T-cell responses but not antibody responses. Notably, the T-cell response induced by the repRNA vaccine was significantly higher than that induced by the nonreplicative RNA vaccine in our experimental model. In the future, it is of the essence to optimize vaccine administration methods and improve S protein expression, like protection of repRNA by nanoparticles and evasion of innate immunity of the host to enhance the immune-inducing ability of the repRNA vaccine.

News from around the RNA world: new avenues in RNA biology, biotechnology and therapeutics from the 2022 SIBBM meeting.

Since the formalization of the Central Dogma of molecular biology, the relevance of RNA in modulating the flow of information from DNA to proteins has been clear. More recently, the discovery of a vast set of non-coding transcripts involved in crucial aspects of cellular biology has renewed the enthusiasm of the RNA community. Moreover, the remarkable impact of RNA therapies in facing the COVID19 pandemics has bolstered interest in the translational opportunities provided by this incredible molecule. For all these reasons, the Italian Society of Biophysics and Molecular Biology (SIBBM) decided to dedicate its 17th yearly meeting, held in June 2022 in Rome, to the many fascinating aspects of RNA biology. More than thirty national and international speakers covered the properties, modes of action and applications of RNA, from its role in the control of development and cell differentiation to its involvement in disease. Here, we summarize the scientific content of the conference, highlighting the take-home message of each presentation, and we stress the directions the community is currently exploring to push forward our comprehension of the RNA World 3.0.

Identification and characterization of virus-encoded circular RNAs in host cells.

Emerging evidence has identified viral circular RNAs (circRNAs) in human cells infected by viruses, interfering with the immune system and inducing diseases including human cancer. However, the biogenesis and regulatory mechanisms of virus-encoded circRNAs in host cells remain unknown. In this study, we used the circRNA detection tool CIRI2 to systematically determine the virus-encoded circRNAs in virus-infected cancer cell lines and cancer patients, by analysing RNA-Seq datasets derived from RNase R-treated samples. Based on the thousands of viral circRNAs we identified, the biological characteristics and potential roles of viral circRNAs in regulating host cell function were determined. In addition, we developed a Viral-circRNA Database (http://www.hywanglab.cn/vcRNAdb/), which is open to all users to search, browse and download information on circRNAs encoded by viruses upon infection.

Noncoding RNome as Enabling Biomarkers for Precision Health.

Noncoding RNAs (ncRNAs), in the form of structural, catalytic or regulatory RNAs, have emerged to be critical effectors of many biological processes. With the advent of new technologies, we have begun to appreciate how intracellular and circulatory ncRNAs elegantly choreograph the regulation of gene expression and protein function(s) in the cell. Armed with this knowledge, the clinical utility of ncRNAs as biomarkers has been recently tested in a wide range of human diseases. In this review, we examine how critical factors govern the success of interrogating ncRNA biomarker expression in liquid biopsies and tissues to enhance our current clinical management of human diseases, particularly in the context of cancer. We also discuss strategies to overcome key challenges that preclude ncRNAs from becoming standard-of-care clinical biomarkers, including sample pre-analytics standardization, data cross-validation with closer attention to discordant findings, as well as correlation with clinical outcomes. Although harnessing multi-modal information from disease-associated noncoding RNome (ncRNome) in biofluids or in tissues using artificial intelligence or machine learning is at the nascent stage, it will undoubtedly fuel the community adoption of precision population health.

RAFFT: Efficient prediction of RNA folding pathways using the fast Fourier transform.

We propose a novel heuristic to predict RNA secondary structure formation pathways that has two components: (i) a folding algorithm and (ii) a kinetic ansatz. This heuristic is inspired by the kinetic partitioning mechanism, by which molecules follow alternative folding pathways to their native structure, some much faster than others. Similarly, our algorithm RAFFT starts by generating an ensemble of concurrent folding pathways ending in multiple metastable structures, which is in contrast with traditional thermodynamic approaches that find single structures with minimal free energies. When we constrained the algorithm to predict only 50 structures per sequence, near-native structures were found for RNA molecules of length ≤ 200 nucleotides. Our heuristic has been tested on the coronavirus frameshifting stimulation element (CFSE): an ensemble of 68 distinct structures allowed us to produce complete folding kinetic trajectories, whereas known methods require evaluating millions of sub-optimal structures to achieve this result. Thanks to the fast Fourier transform on which RAFFT (RNA folding Algorithm wih Fast Fourier Transform) is based, these computations are efficient, with complexity [Formula: see text].

Fluorescent Platforms for RNA Chemical Biology Research.

Efficient detection and observation of dynamic RNA changes remain a tremendous challenge. However, the continuous development of fluorescence applications in recent years enhances the efficacy of RNA imaging. Here we summarize some of these developments from different aspects. For example, single-molecule fluorescence in situ hybridization (smFISH) can detect low abundance RNA at the subcellular level. A relatively new aptamer, Mango, is widely applied to label and track RNA activities in living cells. Molecular beacons (MBs) are valid for quantifying both endogenous and exogenous mRNA and microRNA (miRNA). Covalent binding enzyme labeling fluorescent group with RNA of interest (ROI) partially overcomes the RNA length limitation associated with oligonucleotide synthesis. Forced intercalation (FIT) probes are resistant to nuclease degradation upon binding to target RNA and are used to visualize mRNA and messenger ribonucleoprotein (mRNP) activities. We also summarize the importance of some fluorescence spectroscopic techniques in exploring the function and movement of RNA. Single-molecule fluorescence resonance energy transfer (smFRET) has been employed to investigate the dynamic changes of biomolecules by covalently linking biotin to RNA, and a focus on dye selection increases FRET efficiency. Furthermore, the applications of fluorescence assays in drug discovery and drug delivery have been discussed. Fluorescence imaging can also combine with RNA nanotechnology to target tumors. The invention of novel antibacterial drugs targeting non-coding RNAs (ncRNAs) is also possible with steady-state fluorescence-monitored ligand-binding assay and the T-box riboswitch fluorescence anisotropy assay. More recently, COVID-19 tests using fluorescent clustered regularly interspaced short palindromic repeat (CRISPR) technology have been demonstrated to be efficient and clinically useful. In summary, fluorescence assays have significant applications in both fundamental and clinical research and will facilitate the process of RNA-targeted new drug discovery, therefore deserving further development and updating.

Exploring the multiple conformational states of RNA genome through interhelical dynamics and network analysis.

The structural variation of RNA is often very transient and can be easily missed in experiments. Molecular dynamics simulation studies along with network analysis can be an effective tool to identify prominent conformations of such dynamic biomolecular systems. Here we describe a method to effectively sample different RNA conformations at six different temperatures based on the changes in the interhelical orientations. This method gives the information about prominent states of the RNA as well as the probability of the existence of different conformations and their interconnections during the process of evolution. In the case of the SARS-CoV-2 genome, the change of prominent structures was found to be faster at 333 K as compared to higher temperatures due to the formation of the non-native base pairs. ΔΔG calculated between 288 K and 363 K are found to be 10.31 kcal/mol (88 nt) considering the contribution from the multiple states of the RNA which agrees well with the experimentally reported denaturation energy for E. coli α mRNA pseudoknot (∼16 kcal/mol, 112 nt) determined by calorimetry/UV hyperchromicity and human telomerase RNA telomerase (4.5-6.6 kcal/mol, 54 nt) determined by FRET analysis.

Recent advances in RNA structurome.

RNA structures are essential to support RNA functions and regulation in various biological processes. Recently, a range of novel technologies have been developed to decode genome-wide RNA structures and novel modes of functionality across a wide range of species. In this review, we summarize key strategies for probing the RNA structurome and discuss the pros and cons of representative technologies. In particular, these new technologies have been applied to dissect the structural landscape of the SARS-CoV-2 RNA genome. We also summarize the functionalities of RNA structures discovered in different regulatory layers-including RNA processing, transport, localization, and mRNA translation-across viruses, bacteria, animals, and plants. We review many versatile RNA structural elements in the context of different physiological and pathological processes (e.g., cell differentiation, stress response, and viral replication). Finally, we discuss future prospects for RNA structural studies to map the RNA structurome at higher resolution and at the single-molecule and single-cell level, and to decipher novel modes of RNA structures and functions for innovative applications.

m6A Regulator-Mediated Methylation Modification Patterns and Characteristics in COVID-19 Patients.

Background: RNA N6-methyladenosine (m6A) regulators may be necessary for diverse viral infectious diseases, and serve pivotal roles in various physiological functions. However, the potential roles of m6A regulators in coronavirus disease 2019 (COVID-19) remain unclear. Methods: The gene expression profile of patients with or without COVID-19 was acquired from Gene Expression Omnibus (GEO) database, and bioinformatics analysis of differentially expressed genes was conducted. Random forest modal and nomogram were established to predict the occurrence of COVID-19. Afterward, the consensus clustering method was utilized to establish two different m6A subtypes, and associations between subtypes and immunity were explored. Results: Based on the transcriptional data from GSE157103, we observed that the m6A modification level was markedly enriched in the COVID-19 patients than those in the non-COVID-19 patients. And 18 essential m6A regulators were identified with differential analysis between patients with or without COVID-19. The random forest model was utilized to determine 8 optimal m6A regulators for predicting the emergence of COVID-19. We then established a nomogram based on these regulators, and its predictive reliability was validated by decision curve analysis. The consensus clustering algorithm was conducted to categorize COVID-19 patients into two m6A subtypes from the identified m6A regulators. The patients in cluster A were correlated with activated T-cell functions and may have a superior prognosis. Conclusions: Collectively, m6A regulators may be involved in the prevalence of COVID-19 patients. Our exploration of m6A subtypes may benefit the development of subsequent treatment modalities for COVID-19.

Detection techniques for epitranscriptomic marks.

Similar to epigenetic DNA modification, RNA can be methylated and altered for stability and processing. RNA modifications, namely, epitranscriptomes, involve the following three functions: writing, erasing, and reading of marks. Methods for measurement and position detection are useful for the assessment of cellular function and human disease biomarkers. After pyrimidine 5-methylcytosine was reported for the first time a hundred years ago, numerous techniques have been developed for studying nucleotide modifications, including RNAs. Recent studies have focused on high-throughput and direct measurements for investigating the precise function of epitranscriptomes, including the characterization of severe acute respiratory syndrome coronavirus 2. The current study presents an overview of the development of detection techniques for epitranscriptomic marks and briefs about the recent progress in this field.

Thoughts on how to think (and talk) about RNA structure.

Recent events have pushed RNA research into the spotlight. Continued discoveries of RNA with unexpected diverse functions in healthy and diseased cells, such as the role of RNA as both the source and countermeasure to a severe acute respiratory syndrome coronavirus 2 infection, are igniting a new passion for understanding this functionally and structurally versatile molecule. Although RNA structure is key to function, many foundational characteristics of RNA structure are misunderstood, and the default state of RNA is often thought of and depicted as a single floppy strand. The purpose of this perspective is to help adjust mental models, equipping the community to better use the fundamental aspects of RNA structural information in new mechanistic models, enhance experimental design to test these models, and refine data interpretation. We discuss six core observations focused on the inherent nature of RNA structure and how to incorporate these characteristics to better understand RNA structure. We also offer some ideas for future efforts to make validated RNA structural information available and readily used by all researchers.