Identification of essential filovirion-associated host factors by serial proteomic analysis and RNAi screen

Abstract

An assessment of the total protein composition of filovirus (ebolavirus and marburgvirus) virions is currently lacking. In this study, liquid chromatography-linked tandem mass spectrometry of purified ebola and marburg virions was performed to identify associated cellular proteins. Host proteins involved in cell adhesion, cytoskeleton, cell signaling, intracellular trafficking, membrane organization, and chaperones were identified. Significant overlap exists between this data set and proteomic studies of disparate viruses, including HIV-1 and influenza A, generated in multiple cell types. However, the great majority of proteins identified here have not been previously described to be incorporated within filovirus particles. Host proteins identified by liquid chromatography-linked tandem mass spectrometry could lack biological relevance because they represent protein contaminants in the virus preparation, or because they are incorporated within virions by chance. These issues were addressed using siRNA library-mediated gene knockdown (targeting each identified virion-associated host protein), followed by filovirus infection. Knockdown of several host proteins (e.g. HSPA5 and RPL18) significantly interfered with ebolavirus and marburgvirus infection, suggesting specific and relevant virion incorporation. Notably, select siRNAs inhibited ebolavirus, but enhanced marburgvirus infection, suggesting important differences between the two viruses. The proteomic analysis presented here contributes to a greater understanding of filovirus biology and potentially identifies host factors that can be targeted for antiviral drug development.

Fig. 1.

Virus distribution and gene ontology over-representation analysis for virion-associated host proteins. A, A Venn diagram of virus distribution for the identified virion-associated host proteins is shown. Many more ebola-associated host proteins (EBOV) were identified compared with marburg-associated proteins (MARV). B, Over-representation analysis. For the genes on Table I, observed frequencies of proteins mapping to a particular molecular function, biological process, or biological pathway, were compared with expected frequencies. Several of these gene classifications (on the y axis) were significantly over-represented in Table I, compared with the human genome as a whole. For each group, the expected number of proteins is plotted along with the observed number of proteins with this classification. The Bonferonni-corrected p value is given for each.

Fig. 2.

Strategy to identify true virion-associated host proteins that are essential for viral infection/production. We combined LC-MS/MS proteomic analysis with a siRNA library screen. In addition to host proteins with specific virus incorporation, some proteins detected by LC-MS/MS may be contaminants of the virus preparation, or may be incorporated by chance. The siRNA screen identifies host proteins that are essential for productive virus infection. Ideally, using these techniques in series allows us to priority rank proteins that are likely not contaminants or proteins incorporated by chance.

Fig. 3.

siRNA library screen to identify essential virion-associated host proteins. A, Spot check of siRNA library-mediated transcript knockdown to assess library performance. Following transfection, RNA was isolated from eight wells of the siRNA library. qRT-PCR was performed to measure transcript level. The gene symbol for each gene tested is shown. For each gene, expression level was plotted as a percentage of transcript level for that gene in negative control siRNA (Neg si) treated wells. For simplicity, the Neg si bar for only one gene is shown here. B, Example data from one plate of the siRNA library screen against ebolavirus. Following library transfection and ebola infection, immunostaining was performed to detect cells expressing ebola GP protein. The percentage of infected cells (cells expressing GP) was determined in each well of the library and plotted versus treatment and well position. The data point for HSPA5 siRNA is circled. The vertical line in the graph separates the negative control siRNA wells from the experimental wells. C, Example images from the automated immunofluorescence analysis are shown. Infected cells were detected with a mouse monoclonal antibody to ebola GP, and a green fluorescent secondary antibody. Cell nuclei, stained with Hoechst 33342, are blue.

Fig. 4.

siRNA library screen hits. The siRNA library screen was performed with ebolavirus (EBOV), and marburgvirus (MARV) infection. For each virus, data from replicate plates and repeat experiments were averaged. siRNAs targeting the genes listed here inhibited or enhanced EBOV and/or MARV infection. The numbers shown indicate percent of control infection (nontargeting siRNA transfected wells). Hits shaded green inhibited the infection to ≤50% of control wells. Hits shaded red/dark orange enhanced infection to ≥150% of controls. siRNAs listed here met these criteria for at least one of the viruses.

Fig. 5.

qRT-PCR analysis of target transcripts following siRNA transfection in 293T cells. Four hits from the siRNA screen were chosen for validation. The siRNAs were transfected into 293T cells and RNA was harvested 48 h later. qRT-PCR was performed to examine transcript level for each gene. For each gene, the expression level is plotted as a percentage of transcript level seen in control nontargeting siRNA (Neg si) transfected samples. For simplicity, the Neg si bar for only one gene is shown here. Each siRNA significantly reduced the expression of its target gene at the transcript level.

Fig. 6.

Confirmation of hits from the siRNA library screen. 293T cells were transfected with the indicated siRNAs. Cells were then infected with ebolavirus (A–C), or marburgvirus (D–F). Three days following infection, viral genomic RNA was detected in cell culture supernatants by qRT-PCR (A and D). The number of viral genomic copies per PCR reaction was plotted for each siRNA transfected. On the same plates, the cells were fixed and then processed for immunofluorescence detection of virus infected cells. The average percent infected value (compared with neg si wells) is shown for each siRNA (B and E). From the immunofluorescence analysis, the average number of cells analyzed in each well is also shown (C and F). For the marburgvirus experiment, a lower multiplicity of infection was used in an attempt to clearly observe enhancement of infection. *p < .01.

Fig. 7.

Protein interaction and cellular localization map of filovirion-associated host proteins. For the proteins listed in Table I, cell localization and protein interaction information was examined using Ingenuity Pathways Analysis software. Any protein with an annotation for plasma membrane or lipid raft was placed at this position in the diagram. Approximately half the identified virion-associated proteins are integral membrane, or membrane-associated proteins, and located within or at lipid raft microdomains (red circles). Hits in the siRNA library screen are colored purple (also associated with lipid rafts), or blue (no known lipid raft association). White circles indicate proteins that have no known association with lipid rafts, and also did not score as hits in the siRNA library screen. Literature-described possible protein interactions are indicated by connecting lines.