Identification of RNA-protein interaction networks involved in the norovirus life cycle - PubMed (original) (raw)
Identification of RNA-protein interaction networks involved in the norovirus life cycle
Surender Vashist et al. J Virol. 2012 Nov.
Abstract
Human noroviruses are one of the major causes of acute gastroenteritis in the developed world, yet our understanding of their molecular mechanisms of genome translation and replication lags behind that for many RNA viruses. Due to the nonculturable nature of human noroviruses, many related members of the Caliciviridae family of small RNA viruses are often used as model systems to dissect the finer details of the norovirus life cycle. Murine norovirus (MNV) has provided one such system with which to study the basic mechanisms of norovirus translation and replication in cell culture. In this report we describe the use of riboproteomics to identify host factors that interact with the extremities of the MNV genome. This network of RNA-protein interactions contains many well-characterized host factors, including PTB, La, and DDX3, which have been shown to play a role in the life cycle of other RNA viruses. By using RNA coimmunoprecipitation, we confirmed that a number of the factors identified using riboproteomics are associated with the viral RNA during virus replication in cell culture. We further demonstrated that RNA inhibition-mediated knockdown of the intracellular levels of a number of these factors inhibits or slows norovirus replication in cell culture, allowing identification of new intracellular targets for this important group of pathogens.
Figures
Fig 1
Murine norovirus genome organization and positions of conserved RNA structures. The NS1 to -7 nomenclature, as proposed by Sosnovtsev et al. (66), is presented in italics below the various open reading frames. Note that the RNA structures are not drawn to scale. (A) Predicted RNA structures adopted by the 5′ end of the MNV genome, highlighting the biochemically determined cleavage sites for single-stranded RNA-specific RNases T1, T2, and A, along with the double-stranded RNA-specific RNase V1 cleavage sites. (B) Primary data for RNase sensitivity mapping of the 5′ end of the MNV genome. _In vitro_-transcribed RNA encompassing the region was subjected to limited RNase digestion and subsequent primer extension analysis as described previously. A sequencing ladder prepared using the same primer was also performed to allow the identification of the RNase cleavage sites. Analysis was performed a minimum of 3 times, and 1 representative gel shown. Nucleotide positions are numbered according to their positions in the murine norovirus genome. Note that data are shown for regions containing RNase cleavage sites only. (C) Schematic illustration of the RNA structures adopted by the 3′ 237 nucleotides of the MNV genome. For clarity, the sequence of this region is not shown. The structure shown is as previously computationally predicted and biochemically confirmed (3).
Fig 2
Identification of host factors that interact with the extremities of the murine norovirus genome. Shown are results SDS-PAGE analysis of RNA affinity chromatography-purified host factors that interact with the 5′ or 3′ extremities of the murine norovirus genome, 5′G and 3′Ex, respectively. N/R and beads refer to controls generated using either a nonrelated RNA coupled to cyanogen bromide-activated Sepharose or Sepharose beads alone. (A) Samples purified using S-100 extracts from RAW264.7cells; (B) samples purified using a ribosomal salt wash from rabbit reticulocyte lysates. The positions of proteins enriched in the viral RNA samples compared to the control are highlighted with arrowheads. Note that for clarity only a single gel from each analysis is shown. The protein identities from the data shown are listed in Tables 1 and 2 for the RAW264.7 cells and RRL, respectively.
Fig 3
Network analysis of the host factors found to be associated with the extremities of the murine norovirus genome. The interaction network shows the proteins identified as being associated with the MNV genome by riboproteomics, as described in the text. The proteins shown were identified with a probability greater than 90% and with at least 2 unique peptides showing at least a 90% peptide identification probability. To simplify these interdependencies, host factors that interacted with themselves only or did not interact with other factors in the network are not shown. Proteins shaded in orange were identified using only the the 5′ extremity of MNV genomic RNA and those shaded in blue were identified using the 3′ extremity, while proteins shaded in gray were identified using both RNA targets. Proteins in brackets represent those further characterized during this study. Note that the network was generated using the data presented in Tables 1 and 2 as well as additional experimental data sets. Proteins not identified in the data set illustrated in Fig. 2 and Tables 1 and 2 are highlighted with an asterisk. The interaction network was generated using the Ingenuity Pathway Analysis program (Ingenuity Systems). Full lines represent direct interactions, while dashed lines indicate indirect interactions. An arrow pointing from one protein to another indicates that the first protein acts on or activates the second protein (at which the arrow is pointing).
Fig 4
Host factors interact with the murine norovirus genome during virus replication in cell culture. RAW264.7 cells were infected with MNV-1 at a multiplicity of infection of 1 TCID50 per cell for 15 h, followed by lysis and immunoprecipitation using antisera to either host factors identified using the riboproteomics approach described in the text (anti-HP [αHP]), control rabbit IgG (αCtrl, used for La, PCBP, YBX1, and HSP90), or antisera to GAPDH (αCtrl, used for PTB, DDX3, HuR, and Talin-1). Following immunoprecipitation, any associated RNA was purified, and RT-PCR amplification was performed to identify the presence of viral RNA, as described in the text. An aliquot of the starting material (input) was used to confirm efficient infection and replication.
Fig 5
Confocal analysis of the localization of host factors during murine norovirus replication in cell culture. The murine microglial cell line BV-2 was infected with MNV-1 at a multiplicity of infection of 5 TCID50 per cell, and the infection was allowed to proceed for 12 h. After infection, cells were fixed, permeabilized, and stained with antisera to either the viral protein VPg, viral double-stranded RNA (dsRNA), or various host factors. DAPI staining was used to stain the nuclear DNA. The “Col. points” column highlights the positions of overlapping signals between the viral and cellular antigens generated using the ImageJ colocalization plugin. Bar, 10 μm.
Fig 6
siRNA-mediated reductions in intracellular levels of PTB, La, or DDX3 inhibit murine norovirus. The murine microglial cell line BV-2 was transfected with either nonspecific siRNA (Nsp) or siRNA duplexes targeting La (A), PTB (B), or DDX3 (C). At 12 h posttransfection, the cells were infected with MNV-1 at a multiplicity of infection of 0.5 TCID50 per cell. Total infectious virus production and the levels of viral RNA were then determined at various time points postinfection, as indicated by the TCID50 and RT-quantitative PCR results, respectively. The data were plotted versus the control cells, which were transfected with a nonspecific siRNA control (NSP). In each graph, the percentage value refers to the relative amount of viral RNA or infectious units, expressed as a percentage of the control at that time point. Each experiment was performed using three independent biological repeats and in at least three independent experiments. The data presented are from a single representative data set along with the standard deviations. Western blot analysis was performed using a chemiluminescence-based detection system, and protein expression was quantified using densitometry. In each case, samples were normalized to the levels of GAPDH and the viral NS7 levels expressed relative to the levels observed in cells transfected with nonspecific siRNA control (NSP). Statistical analyses were performed by two-way analysis of variance with Bonferroni's posttest. *, P < 0.05; ***, P < 0.001.
References
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