More than 140 post-transcriptional modifications (PTMs) are known to decorate cellular RNAs, but their incidence, identity and significance in viral RNA are still largely unknown. We have developed an agnostic analytical approach to comprehensively survey PTMs on viral and cellular RNAs. Specifically, we used mass spectrometry to analyze PTMs on total RNA isolated from cells infected with Zika virus, Dengue virus, hepatitis C virus (HCV), poliovirus and human immunodeficiency virus type 1. All five RNA viruses significantly altered global PTM landscapes. Examination of PTM profiles of individual viral genomes isolated by affinity capture revealed a plethora of PTMs on viral RNAs, which far exceeds the handful of well-characterized modifications. Direct comparison of viral epitranscriptomes identified common and virus-specific PTMs. In particular, specific dimethylcytosine modifications were only present in total RNA from virus-infected cells, and in intracellular HCV RNA, and viral RNA from Zika and HCV virions. Moreover, dimethylcytosine abundance during viral infection was modulated by the cellular DEAD-box RNA helicase DDX6. By opening the Pandora’s box on viral PTMs, this report presents numerous questions and hypotheses on PTM function and strongly supports PTMs as a new tier of regulation by which RNA viruses subvert the host and evade cellular surveillance systems.

Flaviviruses limit the cell stress response by preventing the formation of stress granules (SGs) and modulate viral gene expression by subverting different proteins involved in the stress granule pathway. In this study, we investigated the formation of stress granules during Zika virus (ZIKV) infection and the role stress granule proteins play during the viral life cycle. Using immunofluorescence and confocal microscopy, we determined that ZIKV disrupted the formation of arsenite-induced stress granules and changed the subcellular distribution, but not the abundance or integrity, of stress granule proteins. We also investigated the role of different stress granule proteins in ZIKV infection by using target-specific short interfering RNAs to deplete Ataxin2, G3BP1, HuR, TIA-1, TIAR, and YB1. Knockdown of TIA-1 and TIAR affected ZIKV protein and RNA levels but not viral titers. Conversely, depletion of Ataxin2 and YB1 decreased virion production despite having only a small effect on ZIKV protein expression. Notably, however, depletion of G3BP1 and HuR decreased and increased ZIKV gene expression and virion production, respectively. Using an MR766 Gaussia Luciferase reporter genome together with knockdown and overexpression assays, G3BP1 and HuR were found to modulate ZIKV replication. These data indicate that ZIKV disrupts the formation of stress granules by sequestering stress granule proteins required for replication, where G3BP1 functions to promote ZIKV infection while HuR exhibits an antiviral effect. The results of ZIKV relocalizing and subverting select stress granule proteins might have broader consequences on cellular RNA homeostasis and contribute to cellular gene dysregulation and ZIKV pathogenesis. IMPORTANCE Many viruses inhibit SGs. In this study, we observed that ZIKV restricts SG assembly, likely by relocalizing and subverting specific SG proteins to modulate ZIKV replication. This ZIKV-SG protein interaction is interesting, as many SG proteins are also known to function in neuronal granules, which are critical in neural development and function. Moreover, dysregulation of different SG proteins in neurons has been shown to play a role in the progression of neurodegenerative diseases. The likely consequences of ZIKV modulating SG assembly and subverting specific SG proteins are alterations to cellular mRNA transcription, splicing, stability, and translation. Such changes in cellular ribostasis could profoundly affect neural development and contribute to the devastating developmental and neurological anomalies observed following intrauterine ZIKV infection. Our study provides new insights into virus-host interactions and the identification of the SG proteins that may contribute to the unusual pathogenesis associated with this reemerging arbovirus.

Epitranscriptomics, the study of posttranscriptional chemical moieties placed on RNA, has blossomed in recent years. This is due in part to the emergence of high‐throughput detection methods as well as the burst of discoveries showing biological function of select chemical marks. RNA modifications have been shown to affect RNA structure, localization, and functions such as alternative splicing, stabilizing transcripts, nuclear export, cap‐dependent and cap‐independent translation, microRNA biogenesis and binding, RNA degradation, and immune regulation. As such, the deposition of chemical marks on RNA has the unique capability to spatially and temporally regulate gene expression. The goal of this article is to present the exciting convergence of the epitranscriptomic and virology fields, specifically the deposition and biological impact of N7‐methylguanosine, ribose 2′‐O‐methylation, pseudouridine, inosine, N6‐methyladenosine, and 5‐methylcytosine epitranscriptomic marks on gene expression of RNA viruses. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA Interactions with Proteins and Other Molecules > Protein–RNA Interactions: Functional Implications

Chytridiomycosis and ranavirosis are 2 emerging infectious diseases that have caused significant global amphibian decline. Although both have received much scrutiny, little is known about interactions between the 2 causative agents Batrachochytrium dendrobatidis (Bd) and ranavirus (Rv) at the individual host and population levels. We present the first longitudinal assessment of Bd, Rv, and co-infections of a temperate amphibian assemblage in North America. From 2012 to 2016, we assessed the temporal oscillations of Bd, Rv and co-infection dynamics in a sample of 729 animals representing 13 species. Bd, Rv, and co-infected amphibians were detected during all 5 yr. Bd, Rv, and co-infection prevalence all varied annually, with the lowest instances of each at 2.1% (2013), 7.9% (2016), and 0.6% (2016), respectively. The highest Bd, Rv, and co-infection prevalence were recorded in 2012 (26.8%), 2016 (38.3%), and 2015 (10.3%), respectively. There was no association between Bd or Rv infection prevalence and co-infection, either when assessing the entire amphibian assemblage as a whole (odds ratio 1.32, 95% CI: 0.83-2.1, p = 0.29) or within species for amphibians that were more numerically represented (n > 40, p > 0.05). This suggests neither Bd nor Rv facilitate host co-infections within the sampled host assemblage. Instead, the basis for co-infections is the spatiotemporal distribution of both pathogens. Despite lack of interplay between Bd and Rv in this population, our study highlights the importance of considering numerous pathogens that may be present within amphibian habitats in order to properly anticipate interactions that may have direct bearing on disease outcomes.

Hepatitis C virus (HCV) subverts the cellular DEAD-box RNA helicase DDX6 to promote virus infection. Using polysome gradient analysis and the subgenomic HCV Renilla reporter replicon genome, we determined that DDX6 does not affect HCV translation. Rather expression of the subgenomic HCV Renilla luciferase reporter at late times, as well as labeling of newly synthesized viral RNA with 4-thiouridine showed that DDX6 modulates replication. Because DDX6 is an effector protein of the microRNA pathway, we also investigated its role in miR-122-directed HCV gene expression. Similar to sequestering miR-122, depletion of DDX6 modulated HCV RNA stability. Interestingly, miR-122-HCV RNA interaction assays with mutant HCV genomes sites and compensatory exogenous miR-122 showed that DDX6 affects the function of miR-122 at one particular binding site. We propose that DDX6 facilitates the miR-122 interaction with HCV 5′ UTR, which is necessary for stabilizing the viral genome and the switch between translation and replication.

We propose a novel approach for building a classification/identification framework based on the full complement of RNA post-transcriptional modifications (rPTMs) expressed by an organism at basal conditions. The approach relies on advanced mass spectrometry techniques to characterize the products of exonuclease digestion of total RNA extracts. Sample profiles comprising identities and relative abundances of all detected rPTM were used to train and test the capabilities of different machine learning (ML) algorithms. Each algorithm proved capable of identifying rigorous decision rules for differentiating closely related classes and correctly assigning unlabeled samples. The ML classifiers resolved different members of the Enterobacteriaceae family, alternative Escherichia coli serotypes, a series of Saccharomyces cerevisiae knockout mutants, and primary cells of the Homo sapiens central nervous system, which shared very similar genetic backgrounds. The excellent levels of accuracy and resolving power achieved by training on a limited number of classes were successfully replicated when the number of classes was significantly increased to escalate complexity. A dendrogram generated from ML-curated data exhibited a hierarchical organization that closely resembled those afforded by established taxonomic systems. Finer clustering patterns revealed the extensive effects induced by the deletion of a single pivotal gene. This information provided a putative roadmap for exploring the roles of rPTMs in their respective regulatory networks, which will be essential to decipher the epitranscriptomics code. The ubiquitous presence of RNA in virtually all living organisms promises to enable the broadest possible range of applications, with significant implications in the diagnosis of RNA-related diseases.

Introduction: 37 Zika virus (ZIKV) is an enveloped, single-stranded positive-sense RNA virus belonging to the 38 Flaviviridae family, which includes Dengue virus (DENV), Yellow fever virus (YFV), and West Nile 39 virus (WNV) (1). While ZIKV was discovered in Uganda in 1947 (2) , the virus garnered renewed 40 interest during the 2015-2016 outbreak in the Americas (3), in particular because of intrauterine 41 infections and resulting developmental abnormalities such as severe microcephaly, decreased 42 brain tissue, macular scarring, congenital contractures, and hypertonia (4-9). Additionally, adults 43 infected with ZIKV were reported to develop Guillain-Barré syndrome, a debilitating disorder 44 affecting the peripheral nerves (10-13). Similar to other flaviviruses, ZIKV is transmitted by the 45 Aedes aegypti and Aedes albopictus mosquitoes, although recent evidence has shown ZIKV is 46 also capable of sexual and vertical transmission (14-17). While half a century has passed since 47 65 particular, the presence of double-stranded RNA (dsRNA) during viral infection activates protein 66 kinase R (PKR) (19); the accumulation of unfolded proteins in the endoplasmic reticulum (ER) 67 and resulting stress activates PKR-like endoplasmic reticulum kinase (PERK) (20); amino acid 68 starvation activates general control non-repressed 2 (GCN2) (21); and oxidative stress activates 69 5 heme-regulated inhibitor kinase (HRI) (22). Phosphorylation of the a subunit of eIF2 by one of 70 the four stress response kinases results in the stalling of translation initiation, and disassembly of 71 polysomes. Stalled translation initiation complexes bound to mRNA are recognized by several 72 RNA binding proteins, which aggregate to form RNA-protein macromolecular complexes called 73 stress granules (SGs) (23). Once the stressor is abated, eIF2a is dephosphorylated by protein 74 phosphatase 1 (PPI) and the PPI cofactor growth arrest and DNA-damage-inducible 34 75 (GADD34), allowing for the return of sequestered mRNA transcripts to active translation (23). 76 77 SGs are dynamic nonmembrane-bound cytoplasmic structures that can rapidly assemble in 78 response to stress and disassemble once the stress has been alleviated (23). SGs typically 79 contain mRNAs, stalled translation initiation complexes, and numerous RNA binding proteins. 80 Indeed, SGs may contain upwards of 260 different proteins (24), and ~50% of these are proposed 81 to be RNA-binding proteins (25). Of these Ras-GTPase activating binding protein 1 (or GAP SH3 82 domain binding protein 1 [G3BP1]), Caprin1, T-cell internal antigen 1 (TIA-1) and TIA-1 related 83 protein (TIAR) are proposed to be key nucleators of SG assembly (26-29). In addition to 84 translation repression and mRNA sorting, SGs also amplify the innate immune response by 85 aggregating critical antiviral factors (23). Because translation is a critical first step in the flavivirus 86 life cycle, the formation of SGs presents an immediate obstacle to infection. Notably, however, 87 during infection w...

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