Human-pathogen Protein Interactions Illuminated With Bioinformatics
"Infectious diseases result in millions of deaths each year. Although much effort has been directed towards the study of how infection by a pathogen causes disease in humans. We have to leverage the opportunity to compare protein interactions between human and pathogen proteins, from 190 different pathogens to provide important insights into the strategies used by pathogens to infect human cells."
"Previous studies have suggested that protein interaction networks have topologies that are resilient to attacks on random nodes but are susceptible to targeted attacks, for example on hubs. Our results provide a striking example of how pathogens may have evolved the ability to exploit the structure of interactions between human proteins in order to promote infection. This global study also suggests that many viruses share similar strategies to control the human cell cycle, regulate programmed cell death, and transport viral genetic material across the nuclear membrane in the human cell." said one of the investigators
The researchers paid particular attention to two networks of human proteins -- proteins that interact with at least two viral pathogens and proteins that interact with at least two bacterial pathogens. Gene Ontology (GO) terms computed for both sets of proteins provided key information on the functions of the different proteins. Some of the striking findings of the study included a clear demonstration that pathogens preferentially interact with two classes of human proteins referred to as hubs and bottlenecks. Hubs are popular proteins that interact with many other proteins in the human protein interaction network.
Bottlenecks are proteins that lie on many of the shortest paths in the network. Pathogens appear to maximize their likelihood of success by targeting these high-impact, influential proteins during infection. In many cases, human proteins that mediate pathogen effects are proteins that are known to be involved in cancer pathways, for example, the transcription factor STAT1 or the tumor suppressor protein TP53. This finding suggests interesting parallels between pathogen infection and cancer and opens up future areas for research.
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