Two membrane-associated regions within the Nodamura virus RNA-dependent RNA polymerase are critical for both mitochondrial localization and RNA replication.

UNLABELLED: Viruses with positive-strand RNA genomes amplify their genomes in replication complexes associated with cellular membranes. Little is known about the mechanism of replication complex formation in cells infected with Nodamura virus. This virus is unique in its ability to lethally infect both mammals and insects. In mice and in larvae of the greater wax moth (Galleria mellonella), Nodamura virus-infected muscle cells exhibit mitochondrial aggregation and membrane rearrangement, leading to disorganization of the muscle fibrils on the tissue level and ultimately in hind limb/segment paralysis. However, the molecular basis for this pathogenesis and the role of mitochondria in Nodamura virus infection remains unclear. Here, we tested the hypothesis that Nodamura virus establishes RNA replication complexes that associate with mitochondria in mammalian cells. Our results showed that Nodamura virus replication complexes are targeted to mitochondria, as evidenced in biochemical, molecular, and confocal microscopy studies. More specifically, we show that the Nodamura virus RNA-dependent RNA polymerase interacts with the outer mitochondrial membranes as an integral membrane protein and ultimately becomes associated with functional replication complexes. These studies will help us to understand the mechanism of replication complex formation and the pathogenesis of Nodamura virus for mammals. IMPORTANCE: This study will further our understanding of Nodamura virus (NoV) genome replication and its pathogenesis for mice. NoV is unique among the Nodaviridae in its ability to infect mammals. Here we show that NoV establishes RNA replication complexes (RCs) in association with mitochondria in mammalian cells. These RCs contain newly synthesized viral RNA and feature a physical interaction between mitochondrial membranes and the viral RNA-dependent RNA polymerase (RdRp), which is mediated by two membrane-associated regions. While the nature of the interaction needs to be explored further, it appears to occur by a mode distinct from that described for the insect nodavirus Flock House virus (FHV). The interaction of the NoV RdRp with mitochondrial membranes is essential for clustering of mitochondria into networks that resemble those described for infected mouse muscle and that are associated with fatal hind limb paralysis. This work therefore provides the first link between NoV RNA replication complex formation and the pathogenesis of this virus for mice.

Secondary Structure Predictions for Long RNA Sequences Based on Inversion Excursions and MapReduce.

Secondary structures of ribonucleic acid (RNA) molecules play important roles in many biological processes including gene expression and regulation. Experimental observations and computing limitations suggest that we can approach the secondary structure prediction problem for long RNA sequences by segmenting them into shorter chunks, predicting the secondary structures of each chunk individually using existing prediction programs, and then assembling the results to give the structure of the original sequence. The selection of cutting points is a crucial component of the segmenting step. Noting that stem-loops and pseudoknots always contain an inversion, i.e., a stretch of nucleotides followed closely by its inverse complementary sequence, we developed two cutting methods for segmenting long RNA sequences based on inversion excursions: the centered and optimized method. Each step of searching for inversions, chunking, and predictions can be performed in parallel. In this paper we use a MapReduce framework, i.e., Hadoop, to extensively explore meaningful inversion stem lengths and gap sizes for the segmentation and identify correlations between chunking methods and prediction accuracy. We show that for a set of long RNA sequences in the RFAM database, whose secondary structures are known to contain pseudoknots, our approach predicts secondary structures more accurately than methods that do not segment the sequence, when the latter predictions are possible computationally. We also show that, as sequences exceed certain lengths, some programs cannot computationally predict pseudoknots while our chunking methods can. Overall, our predicted structures still retain the accuracy level of the original prediction programs when compared with known experimental secondary structure.

Enhancement of accuracy and efficiency for RNA secondary structure prediction by sequence segmentation and MapReduce.

BACKGROUND: Ribonucleic acid (RNA) molecules play important roles in many biological processes including gene expression and regulation. Their secondary structures are crucial for the RNA functionality, and the prediction of the secondary structures is widely studied. Our previous research shows that cutting long sequences into shorter chunks, predicting secondary structures of the chunks independently using thermodynamic methods, and reconstructing the entire secondary structure from the predicted chunk structures can yield better accuracy than predicting the secondary structure using the RNA sequence as a whole. The chunking, prediction, and reconstruction processes can use different methods and parameters, some of which produce more accurate predictions than others. In this paper, we study the prediction accuracy and efficiency of three different chunking methods using seven popular secondary structure prediction programs that apply to two datasets of RNA with known secondary structures, which include both pseudoknotted and non-pseudoknotted sequences, as well as a family of viral genome RNAs whose structures have not been predicted before. Our modularized MapReduce framework based on Hadoop allows us to study the problem in a parallel and robust environment. RESULTS: On average, the maximum accuracy retention values are larger than one for our chunking methods and the seven prediction programs over 50 non-pseudoknotted sequences, meaning that the secondary structure predicted using chunking is more similar to the real structure than the secondary structure predicted by using the whole sequence. We observe similar results for the 23 pseudoknotted sequences, except for the NUPACK program using the centered chunking method. The performance analysis for 14 long RNA sequences from the Nodaviridae virus family outlines how the coarse-grained mapping of chunking and predictions in the MapReduce framework exhibits shorter turnaround times for short RNA sequences. However, as the lengths of the RNA sequences increase, the fine-grained mapping can surpass the coarse-grained mapping in performance. CONCLUSIONS: By using our MapReduce framework together with statistical analysis on the accuracy retention results, we observe how the inversion-based chunking methods can outperform predictions using the whole sequence. Our chunk-based approach also enables us to predict secondary structures for very long RNA sequences, which is not feasible with traditional methods alone.

A 3' terminal stem-loop structure in Nodamura virus RNA2 forms an essential cis-acting signal for RNA replication.

Nodamura virus (NoV; family Nodaviridae) contains a bipartite positive-strand RNA genome that replicates via negative-strand intermediates. The specific structural and sequence determinants for initiation of nodavirus RNA replication have not yet been identified. For the related nodavirus Flock House virus (FHV) undefined sequences within the 3'-terminal 50 nucleotides (nt) of FHV RNA2 are essential for its replication. We previously showed that a conserved stem-loop structure (3'SL) is predicted to form near the 3' end of the RNA2 segments of seven nodaviruses, including NoV. We hypothesized that the 3'SL structure from NoV RNA2 is an essential cis-acting element for RNA replication. To determine whether the structure can actually form within RNA2, we analyzed the secondary structure of NoV RNA2 in vitro transcripts using nuclease mapping. The resulting nuclease maps were 86% consistent with the predicted 3'SL structure, suggesting that it can form in solution. We used a well-defined reverse genetic system for launch of NoV replication in yeast cells to test the function of the 3'SL in the viral life cycle. Deletion of the nucleotides that comprise the 3'SL from a NoV2-GFP chimeric replicon resulted in a severe defect in RNA2 replication. A minimal replicon containing the 5'-terminal 17 nt and the 3'-terminal 54 nt of RNA2 (including the predicted 3'SL) retained the ability to replicate in yeast, suggesting that this region is able to direct replication of a heterologous mRNA. These data suggest that the 3'SL plays an essential role in replication of NoV RNA2. The conservation of the predicted 3'SL suggests that this common motif may play a role in RNA replication for the other members of the Nodaviridae.

A Dynamic Programming Algorithm for Finding the Optimal Segmentation of an RNA Sequence in Secondary Structure Predictions.

In this paper, we present a dynamic programming algorithm that runs in polynomial time and allows us to achieve the optimal, non-overlapping segmentation of a long RNA sequence into segments (chunks). The secondary structure of each chunk is predicted independently, then combined with the structures predicted for the other chunks, to generate a complete secondary structure prediction that is thus a combination of local energy minima. The proposed approach not only is more efficient and accurate than other traditionally used methods that are based on global energy minimizations, but it also allows scientists to overcome computing and storage constraints when trying to predict the secondary structure of long RNA sequences.

RNAVLab: A virtual laboratory for studying RNA secondary structures based on grid computing technology.

As ribonucleic acid (RNA) molecules play important roles in many biological processes including gene expression and regulation, their secondary structures have been the focus of many recent studies. Despite the computing power of supercomputers, computationally predicting secondary structures with thermodynamic methods is still not feasible when the RNA molecules have long nucleotide sequences and include complex motifs such as pseudoknots. This paper presents RNAVLab (RNA Virtual Laboratory), a virtual laboratory for studying RNA secondary structures including pseudoknots that allows scientists to address this challenge. Two important case studies show the versatility and functionalities of RNAVLab. The first study quantifies its capability to rebuild longer secondary structures from motifs found in systematically sampled nucleotide segments. The extensive sampling and predictions are made feasible in a short turnaround time because of the grid technology used. The second study shows how RNAVLab allows scientists to study the viral RNA genome replication mechanisms used by members of the virus family Nodaviridae.

Nodamura virus RNA replication in Saccharomyces cerevisiae: heterologous gene expression allows replication-dependent colony formation.

Nodamura virus (NoV) and Flock House virus (FHV) are members of the family Nodaviridae. The nodavirus genome is composed of two positive-sense RNA segments: RNA1 encodes the viral RNA-dependent RNA polymerase and RNA2 encodes the capsid protein precursor. A small subgenomic RNA3, which encodes nonstructural proteins B1 and B2, is transcribed from RNA1 during RNA replication. Previously, FHV was shown to replicate both of its genomic RNAs and to transcribe RNA3 in transiently transfected yeast cells. FHV RNAs and their derivatives could also be expressed from plasmids containing RNA polymerase II promoters. Here we show that all of these features can be recapitulated for NoV, the only nodavirus that productively infects mammals. Inducible plasmid-based systems were used to characterize the RNA replication requirements for NoV RNA1 and RNA2 in Saccharomyces cerevisiae. Induced NoV RNA1 replication was robust. Three previously described NoV RNA1 mutants behaved in yeast as they had in mammalian cells. Yeast colonies were selected from cells expressing NoV RNA1, and RNA2 replicons that encoded yeast nutritional markers, from plasmids. Unexpectedly, these NoV RNA replication-dependent yeast colonies were recovered at frequencies 10(4)-fold lower than in the analogous FHV system. Molecular analysis revealed that some of the NoV RNA replication-dependent colonies contained mutations in the NoV B2 open reading frame in the replicating viral RNA. In addition, we found that NoV RNA1 could support limited replication of a deletion derivative of the heterologous FHV RNA2 that expressed the yeast HIS3 selectable marker, resulting in formation of HIS+ colonies.

Nodamura virus nonstructural protein B2 can enhance viral RNA accumulation in both mammalian and insect cells.

During infection of both vertebrate and invertebrate cell lines, the alphanodavirus Nodamura virus (NoV) expresses two nonstructural proteins of different lengths from the B2 open reading frame. The functions of these proteins have yet to be determined, but B2 of the related Flock House virus suppresses RNA interference both in Drosophila cells and in transgenic plants. To examine whether the NoV B2 proteins had similar functions, we compared the replication of wild-type NoV RNA with that of mutants unable to make the B2 proteins. We observed a defect in the accumulation of mutant viral RNA that varied in extent from negligible in some cell lines (e.g., baby hamster kidney cells) to severe in others (e.g., human HeLa and Drosophila DL-1 cells). These results are consistent with the notion that the NoV B2 proteins act to circumvent an innate antiviral response such as RNA interference that differs in efficacy among different host cells.

Interferon antagonist proteins of influenza and vaccinia viruses are suppressors of RNA silencing.

Homology-dependent RNA silencing occurs in many eukaryotic cells. We reported recently that nodaviral infection triggers an RNA silencing-based antiviral response (RSAR) in Drosophila, which is capable of a rapid virus clearance in the absence of expression of a virus-encoded suppressor. Here, we present further evidence to show that the Drosophila RSAR is mediated by the RNA interference (RNAi) pathway, as the viral suppressor of RSAR inhibits experimental RNAi initiated by exogenous double-stranded RNA and RSAR requires the RNAi machinery. We demonstrate that RNAi also functions as a natural antiviral immunity in mosquito cells. We further show that vaccinia virus and human influenza A, B, and C viruses each encode an essential protein that suppresses RSAR in Drosophila. The vaccinia and influenza viral suppressors, E3L and NS1, are distinct double-stranded RNA-binding proteins and essential for pathogenesis by inhibiting the mammalian IFN-regulated innate antiviral response. We found that the double-stranded RNA-binding domain of NS1, implicated in innate immunity suppression, is both essential and sufficient for RSAR suppression. These findings provide evidence that mammalian virus proteins can inhibit RNA silencing, implicating this mechanism as a nucleic acid-based antiviral immunity in mammalian cells.

Recovery of infectivity from cDNA clones of nodamura virus and identification of small nonstructural proteins.

Nodamura virus (NoV) was the first isolated member of the Nodaviridae, and is the type species of the alphanodavirus genus. The alphanodaviruses infect insects; NoV is unique in that it can also lethally infect mammals. Nodaviruses have bipartite positive-sense RNA genomes in which RNA1 encodes the RNA-dependent RNA polymerase and the smaller genome segment, RNA2, encodes the capsid protein precursor. To facilitate the study of NoV, we generated infectious cDNA clones of its two genomic RNAs. Transcription of these NoV1 and NoV2 cDNAs in mammalian cells led to viral RNA replication, protein synthesis, and production of infectious virus. Subgenomic RNA3 was produced during RNA replication and encodes nonstructural proteins B1 and B2 in overlapping ORFs. Site-directed mutagenesis of these ORFs, followed by SDS-PAGE and MALDI-TOF mass spectrometry analyses, showed synthesis of B1 and two forms of B2 (B2-134 and B2-137) during viral replication. We also characterized a point mutation in RNA1 far upstream of the RNA3 region that resulted in decreased RNA3 synthesis and RNA2 replication, and a reduced yield of infectious particles. The ability to reproduce the entire life cycle of this unusual nodavirus from cDNA clones will facilitate further analysis of NoV RNA replication and pathogenesis.

Comparisons among the larger genome segments of six nodaviruses and their encoded RNA replicases.

The Nodaviridae are a family of isometric RNA viruses that infect insects and fish. Their genomes, which are among the smallest known for animal viruses, consist of two co-encapsidated positive-sense RNA segments: RNA1 encodes the viral contribution to the RNA-dependent RNA polymerase (RdRp) which replicates the viral genome, whereas RNA2 encodes the capsid protein precursor. In this study, the RNA1 sequences of two insect nodaviruses - Nodamura virus (the prototype of the genus) and Boolarra virus - are reported as well as detailed comparisons of their encoded RdRps with those of three other nodaviruses of insects and one of fish. Although the 5' and 3' untranslated regions did not reveal common features of RNA sequence or secondary structure, these divergent viruses showed similar genome organizations and encoded RdRps that had from 26 to 99% amino acid sequence identity. All six RdRp amino acid sequences contained canonical RNA polymerase motifs in their C-terminal halves and conserved elements of predicted secondary structure throughout. A search for structural homologues in the protein structure database identified the poliovirus RdRp, 3D(pol), as the best template for homology modelling of the RNA polymerase domain of Pariacoto virus and allowed the construction of a congruent three-dimensional model. These results extend our understanding of the relationships among the RNA1 segments of nodaviruses and the predicted structures of their encoded RdRps.