The human-bacterial pathogen protein interaction networks of Bacillus anthracis, Francisella tularensis, and Yersinia pestis

Abstract

Background: Bacillus anthracis, Francisella tularensis, and Yersinia pestis are bacterial pathogens that can cause anthrax, lethal acute pneumonic disease, and bubonic plague, respectively, and are listed as NIAID Category A priority pathogens for possible use as biological weapons. However, the interactions between human proteins and proteins in these bacteria remain poorly characterized leading to an incomplete understanding of their pathogenesis and mechanisms of immune evasion.

Methodology: In this study, we used a high-throughput yeast two-hybrid assay to identify physical interactions between human proteins and proteins from each of these three pathogens. From more than 250,000 screens performed, we identified 3,073 human-B. anthracis, 1,383 human-F. tularensis, and 4,059 human-Y. pestis protein-protein interactions including interactions involving 304 B. anthracis, 52 F. tularensis, and 330 Y. pestis proteins that are uncharacterized. Computational analysis revealed that pathogen proteins preferentially interact with human proteins that are hubs and bottlenecks in the human PPI network. In addition, we computed modules of human-pathogen PPIs that are conserved amongst the three networks. Functionally, such conserved modules reveal commonalities between how the different pathogens interact with crucial host pathways involved in inflammation and immunity.

Significance: These data constitute the first extensive protein interaction networks constructed for bacterial pathogens and their human hosts. This study provides novel insights into host-pathogen interactions.

Figure 1. Overview of experimental workflow.

A) Overview of analysis pipeline used in this study. B) Venn diagram displaying the number of human proteins interacting with each of the three pathogens in this study.

Figure 2. Network properties of interacting proteins.

Cumulative log-log plots of (A) node centralities and (B) degrees for six subsets of nodes in the whole human protein-protein interaction network: the red curve is for the set of proteins in the human PPI network that do not interact with any pathogen in our dataset; the green line is for the set interacting with B. anthracis; the dark blue line is the for set interacting with F. tularensis; the purple line is for the set interacting with Y. pestis; the light blue line is for the set interacting with at least two pathogens; and the orange line is for the set interacting with all three pathogens. The fraction of proteins at a particular value of degree or centrality is the number of proteins having that value or greater divided by the number of proteins in the set. (Counts in parentheses represent the number of proteins in each set.)

Figure 3. Interactions with host innate immune response.

Interactions of human proteins involved in the innate immune response. We divided the human protein into subsets based on whether they induce or prevent apoptosis, or whether they regulate apoptosis. Proteins in the group labeled “Non-specific” do not have an annotation more specific than “Apoptosis” in the Gene Ontology . For clarity this image shows only interactions involving virulence factors and uncharacterized pathogen proteins. As a result, some human proteins in the figure may appear to have no interacting partners.

Figure 4. Conserved protein interaction modules.

Conserved modules of human-pathogen PPIs involved in (A) antigen binding and processing and (B) immune response pathways. For clarity these images show only the conserved modules from the comparison of B. anthracis and Y. pestis, and interactions involving virulence factors and uncharacterized pathogen proteins. As a result, the human proteins in the figure may appear to be disconnected.

Figure 5. GraphHopper extension of basis CPIM.

An illustration of how GraphHopper expands a CPIM in iteration k. Each image shown two host pathogen PPI networks, one on the left (blue proteins) and one of the right (red proteins). In these images, we do not distinguish between host and pathogen proteins since GraphHopper treats these equally. Solid edges denote PPIs and dashed edges denote orthologs or paralogs. (A) A CPIM at the end of iteration k−1. (B) In iteration k, GraphHopper keeps the network in left side of the CPIM fixed and expands the network in the right side of the CPIM. The two nodes marked by arrows belong to the set P. The node v′ is the lower of these two nodes. GraphHopper adds the thick red interactions and orthology edges to the red network in the CPIM. (C) The CPIM at the end of iteration k.