Korean Journal of Veterinary Service (한국동물위생학회지)

The Korean Society of Veterinary Service (한국동물위생학회)
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Computational approaches for prediction of protein-protein interaction between Foot-and-mouth disease virus and Sus scrofa based on RNA-Seq

  • Park, Tamina (Department of Predictive Toxicology, Korea Institute of Toxicology) ;
  • Kang, Myung-gyun (Department of Predictive Toxicology, Korea Institute of Toxicology) ;
  • Nah, Jinju (Animal and Plant Quarantine Agency) ;
  • Ryoo, Soyoon (Animal and Plant Quarantine Agency) ;
  • Wee, Sunghwan (Animal and Plant Quarantine Agency) ;
  • Baek, Seung-hwa (Department of Predictive Toxicology, Korea Institute of Toxicology) ;
  • Ku, Bokkyung (Animal and Plant Quarantine Agency) ;
  • Oh, Yeonsu (Department of Veterinary Pathology, College of Veterinary Medicine & Institute of Veterinary Science, Kangwon National University) ;
  • Cho, Ho-seong (College of Veterinary Medicine and Bio-safety Research Institute, Chonbuk National University) ;
  • Park, Daeui (Department of Predictive Toxicology, Korea Institute of Toxicology)
  • Received : 2019.04.25
  • Accepted : 2019.05.25
  • Published : 2019.06.30
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Abstract

Foot-and-Mouth Disease (FMD) is a highly contagious trans-boundary viral disease caused by FMD virus, which causes huge economic losses. FMDV infects cloven hoofed (two-toed) mammals such as cattle, sheep, goats, pigs and various wildlife species. To control the FMDV, it is necessary to understand the life cycle and the pathogenesis of FMDV in host. Especially, the protein-protein interaction between FMDV and host will help to understand the survival cycle of viruses in host cell and establish new therapeutic strategies. However, the computational approach for protein-protein interaction between FMDV and pig hosts have not been applied to studies of the onset mechanism of FMDV. In the present work, we have performed the prediction of the pig's proteins which interact with FMDV based on RNA-Seq data, protein sequence, and structure information. After identifying the virus-host interaction, we looked for meaningful pathways and anticipated changes in the host caused by infection with FMDV. A total of 78 proteins of pig were predicted as interacting with FMDV. The 156 interactions include 94 interactions predicted by sequence-based method and the 62 interactions predicted by structure-based method using domain information. The protein interaction network contained integrin as well as STYK1, VTCN1, IDO1, CDH3, SLA-DQB1, FER, and FGFR2 which were related to the up-regulation of inflammation and the down-regulation of cell adhesion and host defense systems such as macrophage and leukocytes. These results provide clues to the knowledge and mechanism of how FMDV affects the host cell.

Keywords

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Fig. 1. The network of interaction between FMDV proteins and DEGs in 3 hpi (A), 6 hpi (B), 12 hpi (C). The green circle indicates FMDV proteins and the others are DEGs among swine (Sus scrofa) proteins. The purple border of the diamond indicates DEGs that were significantly expressed over each FMDV infection time (6 hpi and 12 hpi). A total of 156 direct interactions were predicted. The lines indicates the predicted interaction. The thick lines are predicted with structure- based methods and the others are predicted with sequence-based methods.

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Fig. 2. The linkage of 42 gene ontology terms and 43 related genes (red). The kappa score was set to 0.4 (default) and the network only showed pathways with p-value less than 0.05. The 11 representative terms (total 11 colors) which are merged as redundant groups with ＞50.0% sharing genes were highlighted.

Table 1. The top 10 canonical pathways by significantly up-regulated genes in 6 hpi

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Table 2. The top 10 canonical pathways by significantly down-regulated genes in 6 hpi

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Table 3. The top 10 canonical pathways by significantly up-regulated genes in 12 hpi

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Table 4. The top 10 canonical pathways by significantly down-regulated genes in 12 hpi

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