Phosphoproteomics to Characterize Host Response During H3N2 Canine Influenza Virus Infection of Dog Lung

Abstract

Avian-origin H3N2 canine influenza viruses (CIVs) cause severe contagious respiratory disease in dogs, and quickly adapt to new environments. To further understand the mechanism of virus infection and host-virus interactions, we characterized the complete phosphoproteome of dogs infected with H3N2 CIV. Nine-week-old Beagle dogs were inoculated intranasally with 10⁶ EID₅₀ of A/canine/Guangdong/04/2014 (H3N2) virus. Lung sections were harvested at 5 days post-inoculation (dpi) and processed for global and quantitative analysis of differentially expressed phosphoproteins. A total of 1,235 differentially expressed phosphorylated proteins were identified in the dog lung after H3N2 CIV infection, and 3,016 modification sites were identified among all differentially expressed proteins. We then performed an enrichment analysis of functional annotations using Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) database analyses to predict the functions of the identified differential phosphoproteins. Our data indicate that H3N2 CIV infection causes dramatic changes in the host protein phosphorylation of dog lungs. To our knowledge, this is the first study to assess the effect of H3N2 CIV infection on the phosphoproteome of beagles. These data provide novel insights into H3N2-CIV-triggered regulatory phosphorylation circuits and signaling networks and may improve our understanding of the mechanisms underlying CIV pathogenesis in dogs.

Keywords: H3N2; KEGG; canine influenza; dog; go; phosphoproteomics.

Figure 1

Schematic display of the workflow employed for the phosphoproteomic screen. Extracted proteins were digested with trypsin and were used to enrich peptides phosphorylated on Ser/Thr or Tyr using immobilized metal affinity chromatography (IMAC). Enriched phosphopeptides were analyzed in LC-MS/MS runs, and the original MS/MS file data were submitted to ProteinPilot Software v4.5 for data analysis.

Figure 2

Overview of the identified proteins and phosphopeptides. (A) The distribution of the number of modified sites on the modified protein. One means the number of proteins with only one modification site, two means the number of proteins with only two modification sites, and so on. (B) Proportional distribution of modification sites S, T, Y. (C) Distribution of different peptides. If ratio ≥ 1.5 and p ≤ 0.05, its expression is considered to be significantly up-regulated; if ratio ≤ 0.67 and p ≤ 0.05, its expression is considered to be significantly down-regulated. (D) Comparison group WT: Ctrl volcano map. The red/blue dots on both sides represent the proteins with significant differences in up/down regulation. (E) Hierarchical clustering heat map of differentially phosphorylated peptides. The rows represent the clustering of phosphorylated peptides, and the columns represent the clustering of sample pairs. As the ratio of phosphorylated peptides changes from small to large, the color of the heat map shows a corresponding green-black-red change.

Figure 3

Identification of phosphosite motifs. The phosphorylation site was designated as the center to obtain a peptide sequence of 13 amino acids in total with 6 amino acids on the left and right sides. After removing the repetitions, the modified sequences centered on Ser, Thr and Tyr were analyzed for motif characteristics. When serine and threonine were used as the central modification site, the number of statistically significant motifs were calculated as 29 (A) and 3 (B).

Figure 4

Gene Ontology (GO) classification. The GO classification diagram shows the distribution of the items involved in the three ontologies, and the different colors mark the items involved in the three ontologies. (A) Biological Processes. (B) Cellular Components. (C) Molecular Function.

Figure 5

Differentially phosphorylated protein Pathway enrichment analysis. KEGG is the main public database about Pathway. Through Pathway analysis, the most important biochemical metabolic pathways and signal transduction pathways involved in protein can be determined. (A) Actin cytoskeleton pathway. (B) Focal adhesion pathway.

Figure 6

Cluster of Orthologous Groups of proteins (COG) classification. The abscissa of the figure is the COG entry, and the ordinate is the number of proteins. The figure shows the statistical number of proteins with different functions in the sample.

Figure 7

Differential phosphorylated peptide precursor protein GO enrichment analysis Histogram. (A) Biological Process. (B) Cellular Component. (C) Molecular Function. The abscissa EnrichFactor is the number of differential proteins annotated to this entry and the total number of proteins annotated to this entry.

Figure 8

Differential phosphorylated peptide precursor protein pathway enrichment analysis bubble chart. The ordinate on the left is the name of each functional pathway, and the abscissa is the enrichment factor (the number of differential protein annotations for this functional pathway/the number of total identified protein annotations for this functional pathway).