The domain landscape of virus-host interactomes

Abstract

Viral infections result in millions of deaths in the world today. A thorough analysis of virus-host interactomes may reveal insights into viral infection and pathogenic strategies. In this study, we presented a landscape of virus-host interactomes based on protein domain interaction. Compared to the analysis at protein level, this domain-domain interactome provided a unique abstraction of protein-protein interactome. Through comparisons among DNA, RNA, and retrotranscribing viruses, we identified a core of human domains, that viruses used to hijack the cellular machinery and evade the immune system, which might be promising antiviral drug targets. We showed that viruses preferentially interacted with host hub and bottleneck domains, and the degree and betweenness centrality among three categories of viruses are significantly different. Further analysis at functional level highlighted that different viruses perturbed the host cellular molecular network by common and unique strategies. Most importantly, we creatively proposed a viral disease network among viral domains, human domains and the corresponding diseases, which uncovered several unknown virus-disease relationships that needed further verification. Overall, it is expected that the findings will help to deeply understand the viral infection and contribute to the development of antiviral therapy.

Figure 1

Workflow of the construction and analysis of virus-host interactomes.

Figure 2

Cumulative degree and betweenness centrality distributions. Host domains that are targeted by viruses (targeted) have a higher degree and betweenness centrality than the domains that are not targeted by viruses (nontargeted): (a) degree distribution and (b) betweenness centrality distribution. These findings are statistically significant by Wilcoxon rank sum test. The cumulative frequency at a particular value of degree or centrality is the percent of domains whose degree or centrality are less than this particular value.

Figure 3

Cumulative degree and betweenness centrality distributions among DNA, RNA, and retrotranscribing viruses. Host domains that are targeted by DNA, RNA, and retrotranscribing viruses, respectively, have an approximate degree and betweenness centrality: (a) degree distribution and (b) betweenness centrality distribution. These findings are statistically significant by Fligner-Killeen (median) test. The cumulative frequency at a particular value of degree or centrality is the percent of domains whose degree or centrality are less than this particular value. (c) Topological analysis of the human domains and of the human domains targeted by viruses in the human interactome. The mean degree, the mean betweenness centrality, the mean shortest path length, and mean clustering coefficient are given first for all the human domains, then for the human domains targeted by DNA, RNA, and retrotranscribing viruses.

Figure 4

Cumulative degree distribution of viral domains among DNA, RNA, and retrotranscribing viruses. In the virus-host DDI network, we compared the connectivity of viral domains from DNA, RNA, and retrotranscribing viruses. The finding is statistically significant by Fligner-Killeen (median) test. The cumulative frequency at a particular value of degree is the percent of domains whose degree are less than this particular value.

Figure 5

Viral targets enriched in cancer-related genes. Venn diagram of overlaps among viral target proteins, cancer genes, and a set of top 1000 genes through somatic mutation analysis. P value is based on Fisher's exact test.

Figure 6

Virally implicated diseases network for HCV. Red dot: HCV domains; blue square: HCV target domains; green diamond: host domains regulated by viral targets; purple triangle: tumor sites.