Proteomic analysis of sheep primary testicular cells infected with bluetongue virus

Abstract

Bluetongue virus (BTV) causes a non-contagious, arthropod-transmitted disease in wild and domestic ruminants, such as sheep. In this study, we used iTRAQ labeling coupled with LC-MS/MS for quantitative identification of differentially expressed proteins in BTV-infected sheep testicular (ST) cells. Relative quantitative data were obtained for 4455 proteins in BTV- and mock-infected ST cells, among which 101 and 479 proteins were differentially expressed at 24 and 48 h post-infection, respectively, indicating further proteomic changes during the later stages of infection. Ten corresponding genes of differentially expressed proteins were validated via real-time RT-PCR. Expression levels of three representative proteins, eIF4a1, STAT1 and HSP27, were further confirmed via western blot analysis. Bioinformatics analysis disclosed that the differentially expressed proteins are primarily involved in biological processes related to innate immune response, signal transduction, nucleocytoplasmic transport, transcription and apoptosis. Several upregulated proteins were associated with the RIG-I-like receptor signaling pathway and endocytosis. To our knowledge, this study represents the first attempt to investigate proteome-wide dysregulation in BTV-infected cells with the aid of quantitative proteomics. Our collective results not only enhance understanding of the host response to BTV infection but also highlight multiple potential targets for the development of antiviral agents.

Keywords: BTV; Differential expression; Microbiology; Quantitative proteomics; iTRAQ.

Figure 1

Confirmation of BTV infection in ST cells. (A) Morphological changes in ST cells at different time‐points after BTV infection (MOI = 0.1), with mock‐infected cells as a control. (B) Virus titers of BTV in ST cells expressed as PFU/mL on a logarithmic scale at different times post‐infection. (C) RT‐PCR validation of BTV infection in ST cells by amplifying the S7 gene.

Figure 2

Correlation of uninfected ST cells between the two time‐points (24 and 48 hpi). The x‐axis represents the variation levels of proteins in uninfected ST cells between the two time‐points. The left y‐axis represents the frequency of quantitative proteins (histograms) and the right y‐axis represents the cumulative percentage of proteins at different variation levels (line graph).

Figure 3

Confirmation of differentially expressed proteins with real‐time RT‐PCR or western blot. (A) Real‐time RT‐PCR analysis of ten selected genes in BTV‐infected cells and control samples. ST cells were infected with BTV or mock‐infected at MOI of 0.1, and collected at 24 and 48 hpi. Total RNA was extracted and reverse‐transcribed into cDNA for subsequent analysis via quantitative PCR. Fold‐change values were calculated according to the 2^—ΔΔCT method, using β‐actin as an internal reference. Error bars represent the standard error of three independent experiments. (B) Western blot analysis of β‐actin, STAT1, eIF4a, and HSP27 in BTV‐infected and control samples at 24 and 48 hpi. Equal amounts of protein from BTV and mock‐infected cells were separated using SDS‐PAGE and transferred to PVDF membranes. The membranes were probed with the appropriate antibodies, and bands visualized. β‐actin was used as the internal reference. The images shown are representatives of three independent experiments. (C) The intensity ratio between the corresponding bands (BTV‐infected band/Mock band) was determined using ImageJ and normalized against β‐actin .

Figure 4

GO and KEGG pathway enrichment analysis of 101 differentially expressed proteins based on their functional annotations. (A) Analysis of cellular component (GO‐CC); (B) analysis of molecular function (GO‐MF); (C) analysis of biological process (GO‐BP); (D) KEGG Pathway enrichment analysis.

Figure 5

Interaction network of differentially expressed proteins generated using the STRING database. Network analysis was set at medium confidence (STRING score = 0.4). The edges represent predicted functional associations. An edge was drawn with up to seven different colored lines representing the existence of seven types of evidence used in predicting the associations. The red line indicates the presence of fusion evidence, the green line neighborhood evidence, the blue line co‐occurrence evidence, the purple line experimental evidence, the yellow line textmining evidence, the light‐blue line database evidence, and the black line co‐expression evidence.