Comprehensive mapping of SARS-CoV-2 interactions in vivo reveals functional virus-host interactions

Transcriptomic profiles of monocyte-derived macrophages exposed to SARS-CoV-2 VOCs reveal immune-evasion escape driven by delta

BACKGROUND

Since the breakout of COVID-19, the mutated forms of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have shown enhanced rates of transmission and adaptation to humans. The variants of concern (VOC), designated Alpha, Beta, Gamma, Delta, and Omicron emerged independent of one another, and in turn rapidly became dominant. The success of each VOC, as well as the virus fitness, were enabled by altered intrinsic functional properties and, reasonably, to virus antigenicity changes, conferring the ability to evade a primed immune response.

METHODS

We analysed the gene expression profiles of monocyte-derived macrophages (MDM) isolated from whole blood of healthy participants exposed to the 5 different SARS-CoV-2 VOC: D614G, Alpha (B.1.1.7), Gamma (P1), Delta (B.1.617.2), and Omicron BA.1 (B.1.1.529), and to the HCoV-OC43 strain, a coronavirus already present in the population before the SARS-CoV-2 pandemic. Whole transcriptome RNA-Seq, for both coding and non-coding RNAs, was then made.

RESULTS

After exposure to the 5 VOC of MDM, we initially assessed the presence of the viral SARS-CoV-2 transcripts to confirm viral entry. We then analysed the RNA-Seq data and observed a significant deregulation of both coding and non-coding RNAs. In particular, our RNA-Seq analysis showed a significant up-regulation of several genes involved in different immunological processes, such as PARP9/PARP14 axes, in macrophages exposed to D614G, Alpha, and Gamma variants. Surprisingly, our data showed that macrophages exposed to the Delta variant exhibited a transcriptional profile more similar to the naïve control group, while macrophages exposed to the Omicron variant showed intermediate differentially expressed genes (DEGs) between the two groups. By checking the canonical markers for M1/M2 differentiation states, we did not observe any expression in macrophages exposed to the Delta variant, suggesting an M0 status, comparable to the naïve control group. Finally, we observed a significant deregulation of 3 main types of non-coding RNAs (ncRNAs): long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and small nucleolar RNAs (snoRNAs), some of which are common to coronaviruses, and some specific to SARS-CoV-2.

CONCLUSION

The SARS-CoV-2-dependent alteration of the transcriptome of monocyte-derived macrophage (MDM)-infected cells can be linked to the chronological order of the variants' appearance in the human population. Our data suggest an evolution of VOC in modulating the host immune response, with a strong change in pace beginning with the advent of the Delta variant. MDMs exposed to Delta showed a failure in the activation of the adaptive immune response, and this correlates with the more severe symptoms developed by people affected with this SARS-CoV-2 variant.

A Systems Neuroscience Approach to Diagnosis and Rehabilitation of Post COVID Neurological Syndrome Based on the Systems Neuroscience Test Battery (SNTB) Study Protocol

The proposed study reports the design and development of a rapid screening tool, the Systems Neuroscience Test Battery (SNTB), for diagnosing and evaluating the neurological manifestations of Post-COVID-19 Neurological Syndrome (PCNS) within the broader context of Post-Acute Sequelae to COVID-19 (PASC). The SNTB is designed to incorporate a behaviorally relevant Telehealth component that enhances consumer confidence in symptom discrimination, management of PCNS, and guides rehabilitation programs while allowing for continuous evaluation of intervention effectiveness.The study employs a longitudinal design, with telehealth and routine blood assessments conducted at three-month intervals, including at least two follow-ups post-recruitment. These assessments will involve Consumer-Reported Symptoms, Clinical History, Neuropsychological Data, and Timed Psychophysics, aimed at rapid screening of PCNS-related symptoms including 'brain fog" and its affect on visually driven attention, cognition and visually driven motor behaviors. These assessments are intended to validate the characteristics of 'brain fog' and identify predictive behavioral biomarkers for the development of PCNS.The target population includes adults aged 18-65 who have experienced persistent neurological symptoms for at least three months following a confirmed COVID-19 infection. Exclusion criteria include individuals unable to undergo radiological examinations, such as pregnant women or those with contraindications to MRI, ensuring the robustness of the sample and reducing potential selection bias.The SNTB tool will facilitate the online identification of predictive biomarkers for PCNS and aid in the discovery of effective molecular biomarker combinations for medical intervention and rehabilitation. Complementary to the Telehealth Assessment, hospital facilities will be utilized for radiological and blood-based molecular assessments, ensuring concurrent profiling of structural and functional changes during 'brain fog' and recovery from PCNS symptoms.

CParty: hierarchically constrained partition function of RNA pseudoknots

MOTIVATION

Biologically relevant RNA secondary structures are routinely predicted by efficient dynamic programming algorithms that minimize their free energy. Starting from such algorithms, one can devise partition function algorithms, which enable stochastic perspectives on RNA structure ensembles. As the most prominent example, McCaskill's partition function algorithm is derived from pseudoknot-free energy minimization. While this algorithm became hugely successful for the analysis of pseudoknot-free RNA structure ensembles, as of yet there exists only one pseudoknotted partition function implementation, which covers only simple pseudoknots and comes with a borderline-prohibitive complexity of O(n5) in the RNA length n.

RESULTS

Here, we develop a partition function algorithm corresponding to the hierarchical pseudoknot prediction of HFold, which performs exact optimization in a realistic pseudoknot energy model. In consequence, our algorithm CParty carries over HFold's advantages over classical pseudoknot prediction in characterizing the Boltzmann ensemble at equilibrium. Given an RNA sequence S and a pseudoknot-free structure G, CParty computes the partition function over all possibly pseudoknotted density-2 structures G∪G' of S that extend the fixed G by a disjoint pseudoknot-free structure G'. Thus, CParty follows the common hypothesis of hierarchical pseudoknot formation, where pseudoknots form as tertiary contacts only after a first pseudoknot-free "core" G and we call the computed partition function hierarchically constrained (by G). Like HFold, the dynamic programming algorithm CParty is very efficient, achieving the low complexity of the pseudoknot-free algorithm, i.e. cubic time and quadratic space. Finally, by computing pseudoknotted ensemble energies, we unveil kinetics features of a therapeutic target in SARS-CoV-2.

AVAILABILITY AND IMPLEMENTATION

CParty is available at https://github.com/HosnaJabbari/CParty.

The detection, function, and therapeutic potential of RNA 2'-O-methylation

RNA modifications play crucial roles in shaping RNA structure, function, and metabolism. Their dysregulation has been associated with many diseases, including cancer, developmental disorders, cardiovascular diseases, as well as neurological and immune-related conditions. A particular type of RNA modification, 2'-O-methylation (Nm) stands out due to its widespread occurrence on all four types of nucleotides (A, U, G, C) and in most RNA categories, e.g., mRNA, rRNA, tRNA, miRNA, snRNA, snoRNA, and viral RNA. Nm is the addition of a methyl group to the 2' hydroxyl of the ribose moiety of a nucleoside. Given its great biological significance and reported association with many diseases, we first reviewed the occurrences and functional implications of Nm in various RNA species. We then summarized the reported Nm detection methods, ranging from biochemical techniques in the 70's and 80's to recent methods based on Illumina RNA sequencing, artificial intelligence (AI) models for computational prediction, and the latest nanopore sequencing methods currently under active development. Moreover, we discussed the applications of Nm in the realm of RNA medicine, highlighting its therapeutic potential. At last, we present perspectives on potential research directions, aiming to offer insights for future investigations on Nm modification.

KARR-seq reveals cellular higher-order RNA structures and RNA-RNA interactions

RNA fate and function are affected by their structures and interactomes. However, how RNA and RNA-binding proteins (RBPs) assemble into higher-order structures and how RNA molecules may interact with each other to facilitate functions remain largely unknown. Here we present KARR-seq, which uses N3-kethoxal labeling and multifunctional chemical crosslinkers to covalently trap and determine RNA-RNA interactions and higher-order RNA structures inside cells, independent of local protein binding to RNA. KARR-seq depicts higher-order RNA structure and detects widespread intermolecular RNA-RNA interactions with high sensitivity and accuracy. Using KARR-seq, we show that translation represses mRNA compaction under native and stress conditions. We determined the higher-order RNA structures of respiratory syncytial virus (RSV) and vesicular stomatitis virus (VSV) and identified RNA-RNA interactions between the viruses and the host RNAs that potentially regulate viral replication.

Phase separation and viral factories: unveiling the physical processes supporting RNA packaging in dsRNA viruses

Understanding of the physicochemical properties and functions of biomolecular condensates has rapidly advanced over the past decade. More recently, many RNA viruses have been shown to form cytoplasmic replication factories, or viroplasms, via phase separation of their components, akin to numerous cellular membraneless organelles. Notably, diverse viruses from the Reoviridae family containing 10-12 segmented double-stranded RNA genomes induce the formation of viroplasms in infected cells. Little is known about the inner workings of these membraneless cytoplasmic inclusions and how they may support stoichiometric RNA assembly in viruses with segmented RNA genomes, raising questions about the roles of phase separation in coordinating viral genome packaging. Here, we discuss how the molecular composition of viroplasms determines their properties, highlighting the interplay between RNA structure, RNA remodelling, and condensate self-organisation. Advancements in RNA structural probing and theoretical modelling of condensates can reveal the mechanisms through which these ribonucleoprotein complexes support the selective enrichment and stoichiometric assembly of distinct viral RNAs.

Technological advancements in deciphering RNA-RNA interactions

RNA-RNA interactions (RRIs) can dictate RNA molecules to form intricate higher-order structures and bind their RNA substrates in diverse biological processes. To elucidate the function, binding specificity, and regulatory mechanisms of various RNA molecules, especially the vast repertoire of non-coding RNAs, advanced technologies and methods that globally map RRIs are extremely valuable. In the past decades, many state-of-the-art technologies have been developed for this purpose. This review focuses on those high-throughput technologies for the global mapping of RRIs. We summarize the key concepts and the pros and cons of different technologies. In addition, we highlight the novel biological insights uncovered by these RRI mapping methods and discuss the future challenges for appreciating the crucial roles of RRIs in gene regulation across bacteria, viruses, archaea, and mammals.

Structural and biophysical dissection of RNA conformational ensembles

RNA's ability to form and interconvert between multiple secondary and tertiary structures is critical to its functional versatility and the traditional view of RNA structures as static entities has shifted towards understanding them as dynamic conformational ensembles. In this review we discuss RNA structural ensembles and their dynamics, highlighting the concept of conformational energy landscapes as a unifying framework for understanding RNA processes such as folding, misfolding, conformational changes, and complex formation. Ongoing advancements in cryo-electron microscopy and chemical probing techniques are significantly enhancing our ability to investigate multiple structures adopted by conformationally dynamic RNAs, while traditional methods such as nuclear magnetic resonance spectroscopy continue to play a crucial role in providing high-resolution, quantitative spatial and temporal information. We discuss how these methods, when used synergistically, can provide a comprehensive understanding of RNA conformational ensembles, offering new insights into their regulatory functions.

Protocol for profiling virus-to-host RNA-RNA interactions in infected cells by RIC-seq

Virus-to-host RNA-RNA interactions directly regulate host mRNA stability and viral replication. However, globally profiling virus-to-host in situ RNA-RNA interactions remains challenging. Here, we present an RNA in situ conformation sequencing (RIC-seq)-based protocol for mapping high-confidence virus-to-host in situ RNA-RNA interactions in infected cells. We detail steps for formaldehyde crosslinking, pCp-biotin labeling, in situ proximity ligation, chimeric RNA enrichment, strand-specific library construction, and data analysis. This protocol allows unbiased identification of virus-to-host RNA-RNA interactions for various RNA viruses and is potentially applicable to DNA virus-derived transcripts. For complete details on the use and execution of this protocol, please refer to Zhao et al.1.

Prediction of the effects of the top 10 synonymous mutations from 26645 SARS-CoV-2 genomes of early pandemic phase

Background

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had led to a global pandemic since December 2019. SARS-CoV-2 is a single-stranded RNA virus, which mutates at a higher rate. Multiple works had been done to study nonsynonymous mutations, which change protein sequences. However, there is little study on the effects of SARS-CoV-2 synonymous mutations, which may affect viral fitness. This study aims to predict the effect of synonymous mutations on the SARS-CoV-2 genome.

Methods

A total of 26645 SARS-CoV-2 genomic sequences retrieved from Global Initiative on Sharing all Influenza Data (GISAID) database were aligned using MAFFT. Then, the mutations and their respective frequency were identified. Multiple RNA secondary structures prediction tools, namely RNAfold, IPknot++ and MXfold2 were applied to predict the effect of the mutations on RNA secondary structure and their base pair probabilities was estimated using MutaRNA. Relative synonymous codon usage (RSCU) analysis was also performed to measure the codon usage bias (CUB) of SARS-CoV-2.

Results

A total of 150 synonymous mutations were identified. The synonymous mutation identified with the highest frequency is C3037U mutation in the nsp3 of ORF1a. Of these top 10 highest frequency synonymous mutations, C913U, C3037U, U16176C and C18877U mutants show pronounced changes between wild type and mutant in all 3 RNA secondary structure prediction tools, suggesting these mutations may have some biological impact on viral fitness. These four mutations show changes in base pair probabilities. All mutations except U16176C change the codon to a more preferred codon, which may result in higher translation efficiency.

Conclusion

Synonymous mutations in SARS-CoV-2 genome may affect RNA secondary structure, changing base pair probabilities and possibly resulting in a higher translation rate. However, lab experiments are required to validate the results obtained from prediction analysis.

Experimental Considerations for the Evaluation of Viral Biomolecular Condensates

Biomolecular condensates are nonmembrane-bound assemblies of biological polymers such as protein and nucleic acids. An increasingly accepted paradigm across the viral tree of life is (a) that viruses form biomolecular condensates and (b) that the formation is required for the virus. Condensates can promote viral replication by promoting packaging, genome compaction, membrane bending, and co-opting of host translation. This review is primarily concerned with exploring methodologies for assessing virally encoded biomolecular condensates. The goal of this review is to provide an experimental framework for virologists to consider when designing experiments to (a) identify viral condensates and their components, (b) reconstitute condensation cell free from minimal components, (c) ask questions about what conditions lead to condensation, (d) map these questions back to the viral life cycle, and (e) design and test inhibitors/modulators of condensation as potential therapeutics. This experimental framework attempts to integrate virology, cell biology, and biochemistry approaches.

A single-dose intranasal live-attenuated codon deoptimized vaccine provides broad protection against SARS-CoV-2 and its variants

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) continues its significant health and economic impact globally. Despite the success of spike-protein vaccines in preventing severe disease, long-lasting protection against emerging variants and the prevention of breakthrough infections and transmission remain elusive. We generate an intranasal live-attenuated SARS-CoV-2 vaccine, CDO-7N-1, using codon deoptimization. CDO-7N-1 shows highly attenuated replication and minimal or no lung pathology in vivo over multiple passages. It induces robust mucosal and systemic neutralizing antibody and T-cell subset responses, in mice (female K18-hACE2 and male HFH4-hACE2 mice), hamsters, and macaques triggered by a single immunization. Mice and hamsters vaccinated with CDO-7N-1 are protected from challenge with wild-type (WT) SARS-CoV-2 and other variants of concern. Serum from vaccinated animals neutralizes WT SARS-CoV-2, variants of concern (beta and delta), variants of interest (omicron XBB.1.5) and SARS-CoV-1. Antibody responses are sustained and enhanced by repeated immunization or infection with WT SARS-CoV-2. Immunity against all SARS-CoV-2 proteins by CDO-7N-1 should improve efficacy against future SARS-CoV-2 variants.

Novel Inhibitors of SARS-CoV-2 RNA Identified through Virtual Screening

We currently lack antivirals for most human viruses. In a quest for new molecules, focusing on viral RNA, instead of viral proteins, can represent a promising strategy. In this study, new inhibitors were identified starting from a published crystal structure of the tertiary SARS-CoV-2 RNA involved in the -1 programmed ribosomal frameshift. The pseudoknot structure was refined, and a virtual screening was performed using the repository of binders to the nucleic acid library, taking into consideration RNA flexibility. Hit compounds were validated against the wild-type virus and with a dual-luciferase assay measuring the frameshift efficiency. Several active molecules were identified. Our study reveals new inhibitors of SARS-CoV-2 but also highlights the feasibility of targeting RNA starting from virtual screening, a strategy that could be broadly applied to drug development.

Dynamic label-free analysis of SARS-CoV-2 infection reveals virus-induced subcellular remodeling

Assessing the impact of SARS-CoV-2 on organelle dynamics allows a better understanding of the mechanisms of viral replication. We combine label-free holotomographic microscopy with Artificial Intelligence to visualize and quantify the subcellular changes triggered by SARS-CoV-2 infection. We study the dynamics of shape, position and dry mass of nucleoli, nuclei, lipid droplets and mitochondria within hundreds of single cells from early infection to syncytia formation and death. SARS-CoV-2 infection enlarges nucleoli, perturbs lipid droplets, changes mitochondrial shape and dry mass, and separates lipid droplets from mitochondria. We then used Bayesian network modeling on organelle dry mass states to define organelle cross-regulation networks and report modifications of organelle cross-regulation that are triggered by infection and syncytia formation. Our work highlights the subcellular remodeling induced by SARS-CoV-2 infection and provides an Artificial Intelligence-enhanced, label-free methodology to study in real-time the dynamics of cell populations and their content.

Identification of Hammerhead-variant ribozyme sequences in SARS-CoV-2

The SARS-CoV-2 RNA virus and variants, responsible for the COVID-19 pandemic has become endemic, raised a need for further understanding of the viral genome and biology. Despite vast research on SARS-CoV-2, no ribozymes have been found in the virus genome. Here we report the identification of 39 Hammerhead-variant ribozyme sequences (CoV-HHRz) in SARS-CoV-2. These sequences are highly conserved within SARS-CoV-2 variants but show large diversity among other coronaviruses. In vitro CoV-HHRz sequences possess the characteristics of typical ribozymes; cleavage is pH and ion dependent, although their activity is relatively low and Mn2+ is required for cleavage. The cleavage sites of four CoV-HHRz coincide with the breakpoint of expressed subgenomic RNA (sgRNAs) in SARS-CoV-2 transcriptome data suggesting in vivo activity. The CoV-HHRz are involved in processing sgRNAs for ORF7b, ORF 10 and ORF1ab nsp13 which are essential for viral packaging and life cycle.

Sequence signatures within the genome of SARS-CoV-2 can be used to predict host source

We conducted an in silico analysis to better understand the potential factors impacting host adaptation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in white-tailed deer, humans, and mink due to the strong evidence of sustained transmission within these hosts. Classification models trained on single nucleotide and amino acid differences between samples effectively identified white-tailed deer-, human-, and mink-derived SARS-CoV-2. For example, the balanced accuracy score of Extremely Randomized Trees classifiers was 0.984 ± 0.006. Eighty-eight commonly identified predictive mutations are found at sites under strong positive and negative selective pressure. A large fraction of sites under selection (86.9%) or identified by machine learning (87.1%) are found in genes other than the spike. Some locations encoded by these gene regions are predicted to be B- and T-cell epitopes or are implicated in modulating the immune response suggesting that host adaptation may involve the evasion of the host immune system, modulation of the class-I major-histocompatibility complex, and the diminished recognition of immune epitopes by CD8+ T cells. Our selection and machine learning analysis also identified that silent mutations, such as C7303T and C9430T, play an important role in discriminating deer-derived samples across multiple clades. Finally, our investigation into the origin of the B.1.641 lineage from white-tailed deer in Canada discovered an additional human sequence from Michigan related to the B.1.641 lineage sampled near the emergence of this lineage. These findings demonstrate that machine-learning approaches can be used in combination with evolutionary genomics to identify factors possibly involved in the cross-species transmission of viruses and the emergence of novel viral lineages.IMPORTANCESevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible virus capable of infecting and establishing itself in human and wildlife populations, such as white-tailed deer. This fact highlights the importance of developing novel ways to identify genetic factors that contribute to its spread and adaptation to new host species. This is especially important since these populations can serve as reservoirs that potentially facilitate the re-introduction of new variants into human populations. In this study, we apply machine learning and phylogenetic methods to uncover biomarkers of SARS-CoV-2 adaptation in mink and white-tailed deer. We find evidence demonstrating that both non-synonymous and silent mutations can be used to differentiate animal-derived sequences from human-derived ones and each other. This evidence also suggests that host adaptation involves the evasion of the immune system and the suppression of antigen presentation. Finally, the methods developed here are general and can be used to investigate host adaptation in viruses other than SARS-CoV-2.

Precision nutrition to reset virus-induced human metabolic reprogramming and dysregulation (HMRD) in long-COVID

SARS-CoV-2, the etiological agent of COVID-19, is devoid of any metabolic capacity; therefore, it is critical for the viral pathogen to hijack host cellular metabolic machinery for its replication and propagation. This single-stranded RNA virus with a 29.9 kb genome encodes 14 open reading frames (ORFs) and initiates a plethora of virus-host protein-protein interactions in the human body. These extensive viral protein interactions with host-specific cellular targets could trigger severe human metabolic reprogramming/dysregulation (HMRD), a rewiring of sugar-, amino acid-, lipid-, and nucleotide-metabolism(s), as well as altered or impaired bioenergetics, immune dysfunction, and redox imbalance in the body. In the infectious process, the viral pathogen hijacks two major human receptors, angiotensin-converting enzyme (ACE)-2 and/or neuropilin (NRP)-1, for initial adhesion to cell surface; then utilizes two major host proteases, TMPRSS2 and/or furin, to gain cellular entry; and finally employs an endosomal enzyme, cathepsin L (CTSL) for fusogenic release of its viral genome. The virus-induced HMRD results in 5 possible infectious outcomes: asymptomatic, mild, moderate, severe to fatal episodes; while the symptomatic acute COVID-19 condition could manifest into 3 clinical phases: (i) hypoxia and hypoxemia (Warburg effect), (ii) hyperferritinemia ('cytokine storm'), and (iii) thrombocytosis (coagulopathy). The mean incubation period for COVID-19 onset was estimated to be 5.1 days, and most cases develop symptoms after 14 days. The mean viral clearance times were 24, 30, and 39 days for acute, severe, and ICU-admitted COVID-19 patients, respectively. However, about 25-70% of virus-free COVID-19 survivors continue to sustain virus-induced HMRD and exhibit a wide range of symptoms that are persistent, exacerbated, or new 'onset' clinical incidents, collectively termed as post-acute sequelae of COVID-19 (PASC) or long COVID. PASC patients experience several debilitating clinical condition(s) with >200 different and overlapping symptoms that may last for weeks to months. Chronic PASC is a cumulative outcome of at least 10 different HMRD-related pathophysiological mechanisms involving both virus-derived virulence factors and a multitude of innate host responses. Based on HMRD and virus-free clinical impairments of different human organs/systems, PASC patients can be categorized into 4 different clusters or sub-phenotypes: sub-phenotype-1 (33.8%) with cardiac and renal manifestations; sub-phenotype-2 (32.8%) with respiratory, sleep and anxiety disorders; sub-phenotype-3 (23.4%) with skeleto-muscular and nervous disorders; and sub-phenotype-4 (10.1%) with digestive and pulmonary dysfunctions. This narrative review elucidates the effects of viral hijack on host cellular machinery during SARS-CoV-2 infection, ensuing detrimental effect(s) of virus-induced HMRD on human metabolism, consequential symptomatic clinical implications, and damage to multiple organ systems; as well as chronic pathophysiological sequelae in virus-free PASC patients. We have also provided a few evidence-based, human randomized controlled trial (RCT)-tested, precision nutrients to reset HMRD for health recovery of PASC patients.

An integrative platform for detection of RNA 2'-O-methylation reveals its broad distribution on mRNA

Ribose 2'-O-methylation is involved in critical biological processes, but its biological functions and significance in mRNAs remain underexplored. We have developed NJU-seq, a sensitive method for unbiased 2'-O-methylation (Nm) profiling, and Nm-VAQ, a site-specific quantification tool. Using these tools in tandem, we identified thousands of Nm sites on mRNAs of human and mouse cell lines, of which 68 of 84 selected sites were further validated to be more than 1% 2'-O-methylated. Unlike rRNA, most mRNA Nm sites were from 1% to 30% methylated. In addition, mRNA Nm was dynamic, changing according to the circumstance. Furthermore, we show that fibrillarin is involved as a methyltransferase. By mimicking the detected Nm sites and the context sequence, the RNA fragments could be 2'-O-methylated and demonstrated higher stability but lower translation efficiency. Last, profiling of Nm sites in lung surgery samples revealed common signatures of lung cancer pathogenesis, providing potential new diagnostic markers.

Internal RNA 2'-O-methylation on the HIV-1 genome impairs reverse transcription

Viral RNA genomes are modified by epitranscriptomic marks, including 2'-O-methylation that is added by cellular or viral methyltransferases. 2'-O-Methylation modulates RNA structure, function and discrimination between self- and non-self-RNA by innate immune sensors such as RIG-I-like receptors. This is illustrated by human immunodeficiency virus type-1 (HIV-1) that decorates its RNA genome through hijacking the cellular FTSJ3 2'-O-methyltransferase, thereby limiting immune sensing and interferon production. However, the impact of such an RNA modification during viral genome replication is poorly understood. Here we show by performing endogenous reverse transcription on methylated or hypomethylated HIV-1 particles, that 2'-O-methylation negatively affects HIV-1 reverse transcriptase activity. Biochemical assays confirm that RNA 2'-O-methylation impedes reverse transcriptase activity, especially at low dNTP concentrations reflecting those in quiescent cells, by reducing nucleotide incorporation efficiency and impairing translocation. Mutagenesis highlights K70 as a critical amino acid for the reverse transcriptase to bypass 2'-O-methylation. Hence, the observed antiviral effect due to viral RNA 2'-O-methylation antagonizes the FTSJ3-mediated proviral effects, suggesting the fine-tuning of RNA methylation during viral replication.

RNA structure: implications in viral infections and neurodegenerative diseases

RNA is an intermediary between DNA and protein, a catalyzer of biochemical reactions, and a regulator of genes and transcripts. RNA structures are essential for complicated functions. Recent years have witnessed rapid advancements in RNA secondary structure probing techniques. These technological strides provided comprehensive insights into RNA structures, which significantly contributed to our understanding of diverse cellular regulatory processes, including gene regulation, epigenetic regulation, and post-transactional regulation. Meanwhile, they have facilitated the creation of therapeutic tools for tackling human diseases. Despite their therapeutic applications, RNA structure probing methods also offer a promising avenue for exploring the mechanisms of human diseases, potentially providing the key to overcoming existing research constraints and obtaining the in-depth information necessary for a deeper understanding of disease mechanisms.

2'-OH as a universal handle for studying intracellular RNAs

RNA plays pivotal roles in most cellular processes, serving as both the traditional carrier of genetic information and as a key regulator of cellular functions. The advent of chemical technologies has contributed critically to the analysis of cellular RNA structures, functions, and interactions. Many of these methods and molecules involve the utilization of chemically reactive handles in RNAs, either introduced externally or inherent within the polymer itself. Among these handles, the 2'-hydroxyl (2'-OH) group has emerged as an exceptionally well-suited and general chemical moiety for the modification and profiling of RNAs in intracellular studies. In this review, we provide an overview of the recent advancements in intracellular applications of acylation at the 2'-OH group of RNA. We outline progress made in probing RNA structure and interactomes, controlling RNA function, RNA imaging, and analyzing RNA-small molecule interactions, all achieved in living cells through this simple chemical handle on the biopolymer.

Experimental and computational methods for studying the dynamics of RNA-RNA interactions in SARS-COV2 genomes

Long-range ribonucleic acid (RNA)-RNA interactions (RRI) are prevalent in positive-strand RNA viruses, including Beta-coronaviruses, and these take part in regulatory roles, including the regulation of sub-genomic RNA production rates. Crosslinking of interacting RNAs and short read-based deep sequencing of resulting RNA-RNA hybrids have shown that these long-range structures exist in severe acute respiratory syndrome coronavirus (SARS-CoV)-2 on both genomic and sub-genomic levels and in dynamic topologies. Furthermore, co-evolution of coronaviruses with their hosts is navigated by genetic variations made possible by its large genome, high recombination frequency and a high mutation rate. SARS-CoV-2's mutations are known to occur spontaneously during replication, and thousands of aggregate mutations have been reported since the emergence of the virus. Although many long-range RRIs have been experimentally identified using high-throughput methods for the wild-type SARS-CoV-2 strain, evolutionary trajectory of these RRIs across variants, impact of mutations on RRIs and interaction of SARS-CoV-2 RNAs with the host have been largely open questions in the field. In this review, we summarize recent computational tools and experimental methods that have been enabling the mapping of RRIs in viral genomes, with a specific focus on SARS-CoV-2. We also present available informatics resources to navigate the RRI maps and shed light on the impact of mutations on the RRI space in viral genomes. Investigating the evolution of long-range RNA interactions and that of virus-host interactions can contribute to the understanding of new and emerging variants as well as aid in developing improved RNA therapeutics critical for combating future outbreaks.

The regulation of antiviral innate immunity through non-m6A RNA modifications

The post-transcriptional RNA modifications impact the dynamic regulation of gene expression in diverse biological and physiological processes. Host RNA modifications play an indispensable role in regulating innate immune responses against virus infection in mammals. Meanwhile, the viral RNAs can be deposited with RNA modifications to interfere with the host immune responses. The N6-methyladenosine (m6A) has boosted the recent emergence of RNA epigenetics, due to its high abundance and a transcriptome-wide widespread distribution in mammalian cells, proven to impact antiviral innate immunity. However, the other types of RNA modifications are also involved in regulating antiviral responses, and the functional roles of these non-m6A RNA modifications have not been comprehensively summarized. In this Review, we conclude the regulatory roles of 2'-O-methylation (Nm), 5-methylcytidine (m5C), adenosine-inosine editing (A-to-I editing), pseudouridine (Ψ), N1-methyladenosine (m1A), N7-methylguanosine (m7G), N6,2'-O-dimethyladenosine (m6Am), and N4-acetylcytidine (ac4C) in antiviral innate immunity. We provide a systematic introduction to the biogenesis and functions of these non-m6A RNA modifications in viral RNA, host RNA, and during virus-host interactions, emphasizing the biological functions of RNA modification regulators in antiviral responses. Furthermore, we discussed the recent research progress in the development of antiviral drugs through non-m6A RNA modifications. Collectively, this Review conveys knowledge and inspiration to researchers in multiple disciplines, highlighting the challenges and future directions in RNA epitranscriptome, immunology, and virology.

Small Molecules Targeting Viral RNA

The majority of antivirals available target viral proteins; however, RNA is emerging as a new and promising antiviral target due to the presence of highly structured RNA in viral genomes fundamental for their replication cycle. Here, we discuss methods for the identification of RNA-targeting compounds, starting from the determination of RNA structures either from purified RNA or in living cells, followed by in silico screening on RNA and phenotypic assays to evaluate viral inhibition. Moreover, we review the small molecules known to target the programmed ribosomal frameshifting element of SARS-CoV-2, the internal ribosomal entry site of different viruses, and RNA elements of HIV.

Nanopore sequencing technology and its applications

Since the development of Sanger sequencing in 1977, sequencing technology has played a pivotal role in molecular biology research by enabling the interpretation of biological genetic codes. Today, nanopore sequencing is one of the leading third-generation sequencing technologies. With its long reads, portability, and low cost, nanopore sequencing is widely used in various scientific fields including epidemic prevention and control, disease diagnosis, and animal and plant breeding. Despite initial concerns about high error rates, continuous innovation in sequencing platforms and algorithm analysis technology has effectively addressed its accuracy. During the coronavirus disease (COVID-19) pandemic, nanopore sequencing played a critical role in detecting the severe acute respiratory syndrome coronavirus-2 virus genome and containing the pandemic. However, a lack of understanding of this technology may limit its popularization and application. Nanopore sequencing is poised to become the mainstream choice for preventing and controlling COVID-19 and future epidemics while creating value in other fields such as oncology and botany. This work introduces the contributions of nanopore sequencing during the COVID-19 pandemic to promote public understanding and its use in emerging outbreaks worldwide. We discuss its application in microbial detection, cancer genomes, and plant genomes and summarize strategies to improve its accuracy.

Probing the binding nature and stability of highly transmissible mutated variant alpha to omicron of SARS-CoV-2 RBD with ACE2 via molecular dynamics simulation

Currently, no approved drug is available as a causative agent of coronavirus disease 2019 (COVID-19) except for some repurposed drugs. The first structure of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was reported in late 2019, based on that some vaccines and repurposed drugs were approved to prevent people from COVID-19 during the pandemic situation. Since then, new types of variants emerged and notably, the receptor binding domain (RBD) adopted different binding modes with angiotensin-converting enzyme 2 (ACE2); this made significant changes in the progression of COVID-19. Some of the new variants are highly infectious spreading fast and dangerous. The present study is focused on understanding the binding mode of the RBD of different mutated SARS-CoV-2 variants of concern (alpha to omicron) with the human ACE2 using molecular dynamics simulation. Notably, some variants adopted a new binding mode of RBD with ACE2 and formed different interactions, which is unlike the wild type; this was confirmed from the comparison of interaction between RBD-ACE2 of all variants with its wild-type structure. Binding energy values confirm that some mutated variants exhibit high binding affinity. These findings demonstrate that the variations in the sequence of SARS-CoV-2 S-protein altered the binding mode of RBD; this may be the reason that the virus has high transmissibility and causes new infections. This in-silico study on mutated variants of SARS-CoV-2 RBD with ACE2 insights into their binding mode, binding affinity, and stability. This information may help to understand the RBD-ACE2 binding domains, which allows for designing newer drugs and vaccines.

The Highly Conserved Stem-Loop II Motif Is Dispensable for SARS-CoV-2

The stem-loop II motif (s2m) is an RNA structural element that is found in the 3' untranslated region (UTR) of many RNA viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Though the motif was discovered over 25 years ago, its functional significance is unknown. In order to understand the importance of s2m, we created viruses with deletions or mutations of the s2m by reverse genetics and also evaluated a clinical isolate harboring a unique s2m deletion. Deletion or mutation of the s2m had no effect on growth in vitro or on growth and viral fitness in Syrian hamsters in vivo. We also compared the secondary structure of the 3' UTR of wild-type and s2m deletion viruses using selective 2'-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP) and dimethyl sulfate mutational profiling and sequencing (DMS-MaPseq). These experiments demonstrate that the s2m forms an independent structure and that its deletion does not alter the overall remaining 3'-UTR RNA structure. Together, these findings suggest that s2m is dispensable for SARS-CoV-2. IMPORTANCE RNA viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), contain functional structures to support virus replication, translation, and evasion of the host antiviral immune response. The 3' untranslated region of early isolates of SARS-CoV-2 contained a stem-loop II motif (s2m), which is an RNA structural element that is found in many RNA viruses. This motif was discovered over 25 years ago, but its functional significance is unknown. We created SARS-CoV-2 with deletions or mutations of the s2m and determined the effect of these changes on viral growth in tissue culture and in rodent models of infection. Deletion or mutation of the s2m element had no effect on growth in vitro or on growth and viral fitness in Syrian hamsters in vivo. We also observed no impact of the deletion on other known RNA structures in the same region of the genome. These experiments demonstrate that s2m is dispensable for SARS-CoV-2.

Identification of the viral and cellular microRNA interactomes during SARS-CoV-2 infection

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has had a tremendous impact worldwide. Mapping virus-host interactions is critical to understand disease progression. MicroRNAs (miRNAs) are important RNA regulators, but their interaction with SARS-CoV-2 RNA was not experimentally investigated. Here, using Argonaute (AGO) cross-linking immunoprecipitation combined with RNA proximity ligation (CLEAR-CLIP), we provide unbiased mapping of SARS-CoV-2/miRNA interactions. We identified six main regions on the viral RNA bound primarily by one specific miRNA. Targeted mutagenesis and AGO1-3 knockdown demonstrated that these interactions are not critical for virus production. Moreover, we identified perturbed regulation of cellular miRNA interactions during infection, including non-compensated viral sequestration of the miR-15 family. Transcriptome analysis further showed that mRNAs targeted by this miRNA family are derepressed. This work delineates the interphase between miRNA regulation and SARS-CoV-2 infection and further contributes to deciphering the full molecular interactome of this virus.

Current research on viral proteins that interact with fibrillarin

The nucleolus is a multifunctional nuclear domain primarily dedicated to ribosome biogenesis. Certain viruses developed strategies to manipulate host nucleolar proteins to facilitate their replication by modulating ribosomal RNA (rRNA) processing. This association interferes with nucleolar functions resulting in overactivation or arrest of ribosome biogenesis, induction or inhibition of apoptosis, and affecting stress response. The nucleolar protein fibrillarin (FBL) is an important target of some plant and animal viruses. FBL is an essential and highly conserved S-adenosyl methionine (SAM) dependent methyltransferase, capable of rRNA degradation by its intrinsically disordered region (IDR), the glycine/arginine-rich (GAR) domain. It forms a ribonucleoprotein complex that directs 2'-O-methylations in more than 100 sites of pre-rRNAs. It is involved in multiple cellular processes, including initiation of transcription, oncogenesis, and apoptosis, among others. The interaction with animal viruses, including human viruses, triggered its redistribution to the nucleoplasm and cytoplasm, interfering with its role in pre-rRNA processing. Viral-encoded proteins with IDRs as nucleocapsids, matrix, Tat protein, and even a viral snoRNA, can associate with FBL, forcing the nucleolar protein to undergo atypical functions. Here we review the molecular mechanisms employed by animal and human viruses to usurp FBL functions and the effect on cellular processes, particularly in ribosome biogenesis.

The highly conserved stem-loop II motif is dispensable for SARS-CoV-2

The stem-loop II motif (s2m) is a RNA structural element that is found in the 3' untranslated region (UTR) of many RNA viruses including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Though the motif was discovered over twenty-five years ago, its functional significance is unknown. In order to understand the importance of s2m, we created viruses with deletions or mutations of the s2m by reverse genetics and also evaluated a clinical isolate harboring a unique s2m deletion. Deletion or mutation of the s2m had no effect on growth in vitro , or growth and viral fitness in Syrian hamsters in vivo . We also compared the secondary structure of the 3' UTR of wild type and s2m deletion viruses using SHAPE-MaP and DMS-MaPseq. These experiments demonstrate that the s2m forms an independent structure and that its deletion does not alter the overall remaining 3'UTR RNA structure. Together, these findings suggest that s2m is dispensable for SARS-CoV-2.

IMPORTANCE

RNA viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) contain functional structures to support virus replication, translation and evasion of the host antiviral immune response. The 3' untranslated region of early isolates of SARS-CoV-2 contained a stem-loop II motif (s2m), which is a RNA structural element that is found in many RNA viruses. This motif was discovered over twenty-five years ago, but its functional significance is unknown. We created SARS-CoV-2 with deletions or mutations of the s2m and determined the effect of these changes on viral growth in tissue culture and in rodent models of infection. Deletion or mutation of the s2m element had no effect on growth in vitro , or growth and viral fitness in Syrian hamsters in vivo . We also observed no impact of the deletion on other known RNA structures in the same region of the genome. These experiments demonstrate that the s2m is dispensable for SARS-CoV-2.

Systematic Guidelines for Effective Utilization of COVID-19 Databases in Genomic, Epidemiologic, and Clinical Research

The pandemic has led to the production and accumulation of various types of data related to coronavirus disease 2019 (COVID-19). To understand the features and characteristics of COVID-19 data, we summarized representative databases and determined the data types, purpose, and utilization details of each database. In addition, we categorized COVID-19 associated databases into epidemiological data, genome and protein data, and drug and target data. We found that the data present in each of these databases have nine separate purposes (clade/variant/lineage, genome browser, protein structure, epidemiological data, visualization, data analysis tool, treatment, literature, and immunity) according to the types of data. Utilizing the databases we investigated, we created four queries as integrative analysis methods that aimed to answer important scientific questions related to COVID-19. Our queries can make effective use of multiple databases to produce valuable results that can reveal novel findings through comprehensive analysis. This allows clinical researchers, epidemiologists, and clinicians to have easy access to COVID-19 data without requiring expert knowledge in computing or data science. We expect that users will be able to reference our examples to construct their own integrative analysis methods, which will act as a basis for further scientific inquiry and data searching.

Chemical RNA Cross-Linking: Mechanisms, Computational Analysis, and Biological Applications

In recent years, RNA has emerged as a multifaceted biomolecule that is involved in virtually every function of the cell and is critical for human health. This has led to a substantial increase in research efforts to uncover the many chemical and biological aspects of RNA and target RNA for therapeutic purposes. In particular, analysis of RNA structures and interactions in cells has been critical for understanding their diverse functions and druggability. In the last 5 years, several chemical methods have been developed to achieve this goal, using chemical cross-linking combined with high-throughput sequencing and computational analysis. Applications of these methods resulted in important new insights into RNA functions in a variety of biological contexts. Given the rapid development of new chemical technologies, a thorough perspective on the past and future of this field is provided. In particular, the various RNA cross-linkers and their mechanisms, the computational analysis and challenges, and illustrative examples from recent literature are discussed.

COVID-19 Biogenesis and Intracellular Transport

SARS-CoV-2 is responsible for the COVID-19 pandemic. The structure of SARS-CoV-2 and most of its proteins of have been deciphered. SARS-CoV-2 enters cells through the endocytic pathway and perforates the endosomes' membranes, and its (+) RNA appears in the cytosol. Then, SARS-CoV-2 starts to use the protein machines of host cells and their membranes for its biogenesis. SARS-CoV-2 generates a replication organelle in the reticulo-vesicular network of the zippered endoplasmic reticulum and double membrane vesicles. Then, viral proteins start to oligomerize and are subjected to budding within the ER exit sites, and its virions are passed through the Golgi complex, where the proteins are subjected to glycosylation and appear in post-Golgi carriers. After their fusion with the plasma membrane, glycosylated virions are secreted into the lumen of airways or (seemingly rarely) into the space between epithelial cells. This review focuses on the biology of SARS-CoV-2's interactions with cells and its transport within cells. Our analysis revealed a significant number of unclear points related to intracellular transport in SARS-CoV-2-infected cells.

Structural and Functional RNA Motifs of SARS-CoV-2 and Influenza A Virus as a Target of Viral Inhibitors

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the COVID-19 pandemic, whereas the influenza A virus (IAV) causes seasonal epidemics and occasional pandemics. Both viruses lead to widespread infection and death. SARS-CoV-2 and the influenza virus are RNA viruses. The SARS-CoV-2 genome is an approximately 30 kb, positive sense, 5' capped single-stranded RNA molecule. The influenza A virus genome possesses eight single-stranded negative-sense segments. The RNA secondary structure in the untranslated and coding regions is crucial in the viral replication cycle. The secondary structure within the RNA of SARS-CoV-2 and the influenza virus has been intensively studied. Because the whole of the SARS-CoV-2 and influenza virus replication cycles are dependent on RNA with no DNA intermediate, the RNA is a natural and promising target for the development of inhibitors. There are a lot of RNA-targeting strategies for regulating pathogenic RNA, such as small interfering RNA for RNA interference, antisense oligonucleotides, catalytic nucleic acids, and small molecules. In this review, we summarized the knowledge about the inhibition of SARS-CoV-2 and influenza A virus propagation by targeting their RNA secondary structure.

Effects of natural RNA modifications on the activity of SARS-CoV-2 RNA-dependent RNA polymerase

RNA-dependent RNA polymerase (RdRp) plays a key role in the replication of RNA viruses, including SARS-CoV-2. Processive RNA synthesis by RdRp is crucial for successful genome replication and expression, especially in the case of very long coronaviral genomes. Here, we analysed the activity of SARS-CoV-2 RdRp (the nsp12-nsp7-nsp8 complex) on synthetic primer-templates of various structures, including substrates with mismatched primers or template RNA modifications. It has been shown that RdRp cannot efficiently extend RNA primers containing mismatches and has no intrinsic RNA cleavage activity to remove the primer 3'-end, thus necessitating the action of exoribonuclease for proofreading. Similar to DNA-dependent RNA polymerases, RdRp can perform processive pyrophosphorolysis of the nascent RNA product but this reaction is also blocked in the presence of mismatches. Furthermore, we have demonstrated that several natural post-transcriptional modifications in the RNA template, which do not prevent complementary interactions (N6-methyladenosine, 5-methylcytosine, inosine and pseudouridine), do not change RdRp processivity. At the same time, certain modifications of RNA bases and ribose residues strongly block RNA synthesis, either prior to nucleotide incorporation (3-methyluridine and 1-methylguanosine) or immediately after it (2'-O-methylation). The results demonstrate that the activity of SARS-CoV-2 RdRp can be strongly inhibited by common modifications of the RNA template suggesting a way to design novel antiviral compounds.

Examples of Structural Motifs in Viral Genomes and Approaches for RNA Structure Characterization

The relationship between conserved structural motifs and their biological function in the virus replication cycle is the interest of many researchers around the world. RNA structure is closely related to RNA function. Therefore, technological progress in high-throughput approaches for RNA structure analysis and the development of new ones are very important. In this mini review, we discuss a few perspectives on the structural elements of viral genomes and some methods used for RNA structure prediction and characterization. Based on the recent literature, we describe several examples of studies concerning the viral genomes, especially severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza A virus (IAV). Herein, we emphasize that a better understanding of viral genome architecture allows for the discovery of the structure-function relationship, and as a result, the discovery of new potential antiviral therapeutics.

SARSNTdb database: Factors affecting SARS-CoV-2 sequence conservation

SARSNTdb offers a curated, nucleotide-centric database for users of varying levels of SARS-CoV-2 knowledge. Its user-friendly interface enables querying coding regions and coordinate intervals to find out the various functional and selective constraints that act upon the corresponding nucleotides and amino acids. Users can easily obtain information about viral genes and proteins, functional domains, repeats, secondary structure formation, intragenomic interactions, and mutation prevalence. Currently, many databases are focused on the phylogeny and amino acid substitutions, mainly in the spike protein. We took a novel, more nucleotide-focused approach as RNA does more than just code for proteins and many insights can be gleaned from its study. For example, RNA-targeted drug therapies for SARS-CoV-2 are currently being developed and it is essential to understand the features only visible at that level. This database enables the user to identify regions that are more prone to forming secondary structures that drugs can target. SARSNTdb also provides illustrative mutation data from a subset of ~25,000 patient samples with a reliable read coverage across the whole genome (from different locations and time points in the pandemic. Finally, the database allows for comparing SARS-CoV-2 and SARS-CoV domains and sequences. SARSNTdb can serve the research community by being a curated repository for information that gives a jump start to analyze a mutation’s effect far beyond just determining synonymous/non-synonymous substitutions in protein sequences.

Single-cell RNA-sequencing data analysis reveals a highly correlated triphasic transcriptional response to SARS-CoV-2 infection

Single-cell RNA sequencing (scRNA-seq) is currently one of the most powerful techniques available to study the transcriptional response of thousands of cells to an external perturbation. Here, we perform a pseudotime analysis of SARS-CoV-2 infection using publicly available scRNA-seq data from human bronchial epithelial cells and colon and ileum organoids. Our results reveal that, for most genes, the transcriptional response to SARS-CoV-2 infection follows a non-linear pattern characterized by an initial and a final down-regulatory phase separated by an intermediate up-regulatory stage. A correlation analysis of transcriptional profiles suggests a common mechanism regulating the mRNA levels of most genes. Interestingly, genes encoded in the mitochondria or involved in translation exhibited distinct pseudotime profiles. To explain our results, we propose a simple model where nuclear export inhibition of nsp1-sensitive transcripts will be sufficient to explain the transcriptional shutdown of SARS-CoV-2 infected cells.

SARS-CoV-2 Inhibitors Identified by Phenotypic Analysis of a Collection of Viral RNA-Binding Molecules

Antiviral agents are needed for the treatment of SARS-CoV-2 infections and to control other coronavirus outbreaks that may occur in the future. Here we report the identification and characterization of RNA-binding compounds that inhibit SARS-CoV-2 replication. The compounds were detected by screening a small library of antiviral compounds previously shown to bind HIV-1 or HCV RNA elements with a live-virus cellular assay detecting inhibition of SARS-CoV-2 replication. These experiments allowed detection of eight compounds with promising anti-SARS-CoV-2 activity in the sub-micromolar to micromolar range and wide selectivity indexes. Examination of the mechanism of action of three selected hit compounds excluded action on the entry or egress stages of the virus replication cycle and confirmed recognition by two of the molecules of conserved RNA elements of the SARS-CoV-2 genome, including the highly conserved S2m hairpin located in the 3'-untranslated region of the virus. While further studies are needed to clarify the mechanism of action responsible for antiviral activity, these results facilitate the discovery of RNA-targeted antivirals and provide new chemical scaffolds for developing therapeutic agents against coronaviruses.

Discovery of host-directed modulators of virus infection by probing the SARS-CoV-2-host protein-protein interaction network

The ongoing coronavirus disease 2019 (COVID-19) pandemic has highlighted the need to better understand virus-host interactions. We developed a network-based method that expands the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-host protein interaction network and identifies host targets that modulate viral infection. To disrupt the SARS-CoV-2 interactome, we systematically probed for potent compounds that selectively target the identified host proteins with high expression in cells relevant to COVID-19. We experimentally tested seven chemical inhibitors of the identified host proteins for modulation of SARS-CoV-2 infection in human cells that express ACE2 and TMPRSS2. Inhibition of the epigenetic regulators bromodomain-containing protein 4 (BRD4) and histone deacetylase 2 (HDAC2), along with ubiquitin-specific peptidase (USP10), enhanced SARS-CoV-2 infection. Such proviral effect was observed upon treatment with compounds JQ1, vorinostat, romidepsin and spautin-1, when measured by cytopathic effect and validated by viral RNA assays, suggesting that the host proteins HDAC2, BRD4 and USP10 have antiviral functions. We observed marked differences in antiviral effects across cell lines, which may have consequences for identification of selective modulators of viral infection or potential antiviral therapeutics. While network-based approaches enable systematic identification of host targets and selective compounds that may modulate the SARS-CoV-2 interactome, further developments are warranted to increase their accuracy and cell-context specificity.

Internal RNA 2′O-methylation in the HIV-1 genome counteracts ISG20 nuclease-mediated antiviral effect

RNA 2′O-methylation is a ‘self’ epitranscriptomic modification allowing discrimination between host and pathogen. Indeed, human immunodeficiency virus 1 (HIV-1) induces 2′O-methylation of its genome by recruiting the cellular FTSJ3 methyltransferase, thereby impairing detection by RIG-like receptors. Here, we show that RNA 2′O-methylations interfere with the antiviral activity of interferon-stimulated gene 20-kDa protein (ISG20). Biochemical experiments showed that ISG20-mediated degradation of 2′O-methylated RNA pauses two nucleotides upstream of and at the methylated residue. Structure-function analysis indicated that this inhibition is due to steric clash between ISG20 R53 and D90 residues and the 2′O-methylated nucleotide. We confirmed that hypomethylated HIV-1 genomes produced in FTSJ3-KO cells were more prone to in vitro degradation by ISG20 than those produced in cells expressing FTSJ3. Finally, we found that reverse-transcription of hypomethylated HIV-1 was impaired in T cells by interferon-induced ISG20, demonstrating the direct antagonist effect of 2′O-methylation on ISG20-mediated antiviral activity.

Assessing the Drawbacks and Benefits of Ion Migration in Lead Halide Perovskites

Since the inception of the unprecedented rise of halide perovskites for photovoltaic research, ion migration has shadowed this material class with undesirable hysteresis and degradation effects, limiting its practical implementations. Unfortunately, the localized doping and electrochemical reactions triggered by ion migration cause many more undesirable effects that are often unreported or misinterpreted because they deviate from classical semiconductor behavior. In this Perspective, we provide a concise overview of such effects in halide perovskites, such as operational instability in photovoltaics, polarization-induced abnormal external quantum efficiency in light-emitting diodes, and energy channel shift and anomalous sensitivities in hard radiation detection. Finally, we highlight a unique use case of exploiting ion migration as a boon to design emerging memory technologies such as memristors for information storage and computing.

CovInter: interaction data between coronavirus RNAs and host proteins

Coronavirus has brought about three massive outbreaks in the past two decades. Each step of its life cycle invariably depends on the interactions among virus and host molecules. The interaction between virus RNA and host protein (IVRHP) is unique compared to other virus-host molecular interactions and represents not only an attempt by viruses to promote their translation/replication, but also the host's endeavor to combat viral pathogenicity. In other words, there is an urgent need to develop a database for providing such IVRHP data. In this study, a new database was therefore constructed to describe the interactions between coronavirus RNAs and host proteins (CovInter). This database is unique in (a) unambiguously characterizing the interactions between virus RNA and host protein, (b) comprehensively providing experimentally validated biological function for hundreds of host proteins key in viral infection and (c) systematically quantifying the differential expression patterns (before and after infection) of these key proteins. Given the devastating and persistent threat of coronaviruses, CovInter is highly expected to fill the gap in the whole process of the 'molecular arms race' between viruses and their hosts, which will then aid in the discovery of new antiviral therapies. It's now free and publicly accessible at: https://idrblab.org/covinter/.

COVID-19 metabolism: Mechanisms and therapeutic targets

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) dysregulates antiviral signaling, immune response, and cell metabolism in human body. Viral genome and proteins hijack host metabolic network to support viral biogenesis and propagation. However, the regulatory mechanism of SARS-CoV-2-induced metabolic dysfunction has not been elucidated until recently. Multiomic studies of coronavirus disease 2019 (COVID-19) revealed an intensive interaction between host metabolic regulators and viral proteins. SARS-CoV-2 deregulated cellular metabolism in blood, intestine, liver, pancreas, fat, and immune cells. Host metabolism supported almost every stage of viral lifecycle. Strikingly, viral proteins were found to interact with metabolic enzymes in different cellular compartments. Biochemical and genetic assays also identified key regulatory nodes and metabolic dependencies of viral replication. Of note, cholesterol metabolism, lipid metabolism, and glucose metabolism are broadly involved in viral lifecycle. Here, we summarized the current understanding of the hallmarks of COVID-19 metabolism. SARS-CoV-2 infection remodels host cell metabolism, which in turn modulates viral biogenesis and replication. Remodeling of host metabolism creates metabolic vulnerability of SARS-CoV-2 replication, which could be explored to uncover new therapeutic targets. The efficacy of metabolic inhibitors against COVID-19 is under investigation in several clinical trials. Ultimately, the knowledge of SARS-CoV-2-induced metabolic reprogramming would accelerate drug repurposing or screening to combat the COVID-19 pandemic.

Detecting RNA-RNA interactome

The last decade has seen a robust increase in various types of novel RNA molecules and their complexity in gene regulation. RNA molecules play a critical role in cellular events by interacting with other biomolecules, including protein, DNA, and RNA. It has been established that RNA-RNA interactions play a critical role in several biological processes by regulating the biogenesis and function of RNA molecules. Interestingly, RNA-RNA interactions regulate the biogenesis of diverse RNA molecules, including mRNAs, microRNAs, tRNAs, and circRNAs, through splicing or backsplicing. Structured RNAs like rRNA, tRNA, and snRNAs achieve their functional conformation by intramolecular RNA-RNA interactions. In addition, functional consequences of many intermolecular RNA-RNA interactions have been extensively studied in the regulation of gene expression. Hence, it is essential to understand the mechanism and functions of RNA-RNA interactions in eukaryotes. Conventionally, RNA-RNA interactions have been identified through diverse biochemical methods for decades. The advent of high-throughput RNA-sequencing technologies has revolutionized the identification of global RNA-RNA interactome in cells and their importance in RNA structure and function in gene expression regulation. Although these technologies revealed tens of thousands of intramolecular and intermolecular RNA-RNA interactions, we further look forward to future unbiased and quantitative high-throughput technologies for detecting transcriptome-wide RNA-RNA interactions. With the ability to detect RNA-RNA interactome, we expect that future studies will reveal the higher-order structures of RNA molecules and multi-RNA hybrids impacting human health and diseases. This article is categorized under: RNA Methods > RNA Analyses In Vitro and In Silico RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems.

Computational and Experimental Approaches to Study the RNA Secondary Structures of RNA Viruses

Most pandemics of recent decades can be traced to RNA viruses, including HIV, SARS, influenza, dengue, Zika, and SARS-CoV-2. These RNA viruses impose considerable social and economic burdens on our society, resulting in a high number of deaths and high treatment costs. As these RNA viruses utilize an RNA genome, which is important for different stages of the viral life cycle, including replication, translation, and packaging, studying how the genome folds is important to understand virus function. In this review, we summarize recent advances in computational and high-throughput RNA structure-mapping approaches and their use in understanding structures within RNA virus genomes. In particular, we focus on the genome structures of the dengue, Zika, and SARS-CoV-2 viruses due to recent significant outbreaks of these viruses around the world.

Lessons Learned and Yet-to-Be Learned on the Importance of RNA Structure in SARS-CoV-2 Replication

SARS-CoV-2, the etiological agent responsible for the COVID-19 pandemic, is a member of the virus family Coronaviridae, known for relatively extensive (~30-kb) RNA genomes that not only encode for numerous proteins but are also capable of forming elaborate structures. As highlighted in this review, these structures perform critical functions in various steps of the viral life cycle, ultimately impacting pathogenesis and transmissibility. We examine these elements in the context of coronavirus evolutionary history and future directions for curbing the spread of SARS-CoV-2 and other potential human coronaviruses. While we focus on structures supported by a variety of biochemical, biophysical, and/or computational methods, we also touch here on recent evidence for novel structures in both protein-coding and noncoding regions of the genome, including an assessment of the potential role for RNA structure in the controversial finding of SARS-CoV-2 integration in “long COVID” patients. This review aims to serve as a consolidation of previous works on coronavirus and more recent investigation of SARS-CoV-2, emphasizing the need for improved understanding of the role of RNA structure in the evolution and adaptation of these human viruses.

RNAvigator: A Pipeline to Identify Candidates for Functional RNA Structure Elements

Identifying structural elements in long and complex RNAs, such as long non-coding and RNA viruses, can shed light on the functionality and mechanisms of such RNAs. Here we present RNAvigator, a tool able to identify elements of structural importance by using experimental SHAPE data or SHAPE-like predictions in conjunction with stability and entropy assessments. RNAvigator recognizes regions that are the most stable, unambiguous, and structured on RNA molecules, and thus potentially functional. When relying on predictions, RNAvigator uses the CROSS algorithm, a neural network trained on experimental data that achieved an AUC of 0.74 on hepatitis C virus SHAPE-MaP data and which was able to improve the predictive power of Superfold. By using RNAvigator, we can identify known functional regions on the complete hepatitis C virus genome, including the regulatory regions CRE and IRES, and the 3’ UTR of dengue virus, a region known for the presence of structural elements essential for its replication, and functional regions of long non-coding RNAs such as XIST and HOTAIR. We envision that RNAvigator will be a useful tool for studying long and complex RNA molecules using known chemical probing data or, if they are not available, by employing predicted profiles.

The snoGloBe interaction predictor reveals a broad spectrum of C/D snoRNA RNA targets

Box C/D small nucleolar RNAs (snoRNAs) are a conserved class of RNA known for their role in guiding ribosomal RNA 2'-O-ribose methylation. Recently, C/D snoRNAs were also implicated in regulating the expression of non-ribosomal genes through different modes of binding. Large scale RNA-RNA interaction datasets detect many snoRNAs binding messenger RNA, but are limited by specific experimental conditions. To enable a more comprehensive study of C/D snoRNA interactions, we created snoGloBe, a human C/D snoRNA interaction predictor based on a gradient boosting classifier. SnoGloBe considers the target type, position and sequence of the interactions, enabling it to outperform existing predictors. Interestingly, for specific snoRNAs, snoGloBe identifies strong enrichment of interactions near gene expression regulatory elements including splice sites. Abundance and splicing of predicted targets were altered upon the knockdown of their associated snoRNA. Strikingly, the predicted snoRNA interactions often overlap with the binding sites of functionally related RNA binding proteins, reinforcing their role in gene expression regulation. SnoGloBe is also an excellent tool for discovering viral RNA targets, as shown by its capacity to identify snoRNAs targeting the heavily methylated SARS-CoV-2 RNA. Overall, snoGloBe is capable of identifying experimentally validated binding sites and predicting novel sites with shared regulatory function.

Epitranscriptomics of SARS-CoV-2 Infection

Recent studies on the epitranscriptomic code of SARS-CoV-2 infection have discovered various RNA modifications, such as N6-methyladenosine (m6A), pseudouridine (Ψ), and 2′-O-methylation (Nm). The effects of RNA methylation on SARS-CoV-2 replication and the enzymes involved in this mechanism are emerging. In this review, we summarize the advances in this emerging field and discuss the role of various players such as readers, writers, and erasers in m6A RNA methylation, the role of pseudouridine synthase one and seven in epitranscriptomic modification Ψ, an isomer of uridine, and role of nsp16/nsp10 heterodimer in 2′-O-methylation of the ribose sugar of the first nucleotide of SARS-CoV-2 mRNA. We also discuss RNA expression levels of various enzymes involved in RNA modifications in blood cells of SARS-CoV-2 infected individuals and their impact on host mRNA modification. In conclusion, these observations will facilitate the development of novel strategies and therapeutics for targeting RNA modification of SARS-CoV-2 RNA to control SARS-CoV-2 infection.