Infection Strategies of Bacterial and Viral Pathogens through Pathogen-Human Protein-Protein Interactions

Abstract

Since ancient times, even in today's modern world, infectious diseases cause lots of people to die. Infectious organisms, pathogens, cause diseases by physical interactions with human proteins. A thorough analysis of these interspecies interactions is required to provide insights about infection strategies of pathogens. Here we analyzed the most comprehensive available pathogen-human protein interaction data including 23,435 interactions, targeting 5,210 human proteins. The data were obtained from the newly developed pathogen-host interaction search tool, PHISTO. This is the first comprehensive attempt to get a comparison between bacterial and viral infections. We investigated human proteins that are targeted by bacteria and viruses to provide an overview of common and special infection strategies used by these pathogen types. We observed that in the human protein interaction network the proteins targeted by pathogens have higher connectivity and betweenness centrality values than those proteins not interacting with pathogens. The preference of interacting with hub and bottleneck proteins is found to be a common infection strategy of all types of pathogens to manipulate essential mechanisms in human. Compared to bacteria, viruses tend to interact with human proteins of much higher connectivity and centrality values in the human network. Gene Ontology enrichment analysis of the human proteins targeted by pathogens indicates crucial clues about the infection mechanisms of bacteria and viruses. As the main infection strategy, bacteria interact with human proteins that function in immune response to disrupt human defense mechanisms. Indispensable viral strategy, on the other hand, is the manipulation of human cellular processes in order to use that transcriptional machinery for their own genetic material transcription. A novel observation about pathogen-human systems is that the human proteins targeted by both pathogens are enriched in the regulation of metabolic processes.

Keywords: PHISTO; bottleneck; gene ontology; hub; infection strategy; pathogen–human protein–protein interactions.

Figure 1

The number of pathogen-targeted human proteins that are grouped based on their interactions with viruses, bacteria, and fungi – protozoa (targeted by fungi and/or protozoa).

Figure 2

The cumulative degree distributions of human protein sets. The distribution of all proteins in the PPI network is given in comparison with (A) the bacteria-targeted sets, and (B) the virus-targeted sets. The number of proteins in each set is given in the parentheses. The fraction of proteins at a particular value of degree is the number of proteins having that value and greater divided by the number of proteins in the set.

Figure 3

The cumulative betweenness centrality distributions of human protein sets. The distribution of all proteins in the PPI network is given in comparison with (A) the bacteria-targeted sets, and (B) the virus-targeted sets. The number of proteins in each set is given in the parentheses. The fraction of proteins at a particular value of betweenness centrality is the number of proteins having that value and greater divided by the number of proteins in the set.

Figure 4

The cumulative distributions of degree and betweenness centrality of human proteins excluding Yersinia and HIV data. The number of proteins in each set is given in the parentheses. (A) The degree distributions (B) the betweenness centrality distributions. The fraction of proteins at a particular value of degree is the number of proteins having that value and greater divided by the number of proteins in the set.