PLoS BiologyBioinformaticsPeer-reviewed journal article
Consensus clustering of herpesvirus protein interaction networks provides insights into their evolutionary relationship with bacteriophages
Anna Hernández Durán, Todd M. GrecoiD, Benjamin VollmeriD, Ileana M. CristeaiD, Kay GrünewaldiD, Maya TopfiD
Abstract
Infections with human herpesviruses are ubiquitous and a public health concern worldwide. Current treatments reduce the morbidity of some manifested symptoms but neither remove the viral reservoir from the infected host nor protect from the recurrent symptom outbreaks that characterize herpetic infections. The difficulty in therapeutically tackling these viral systems stems in part from their remarkably large proteomes and the complex networks of physical and functional associations that they tailor. This study presents our efforts to unravel the complexity of the interactome of herpes simplex virus type 1 (HSV1), the prototypical herpesvirus species. Inspired by our previous work, we present an improved computational pipeline for the protein-protein interaction (PPI) network reconstruction in HSV1, combining both experimentally supported and bioinformatic predictions. Our newly-developed consensus clustering approach allows us to extend the analysis beyond binary physical interactions and reveals higher order functional associations including that of pUS10 with capsid proteins. In-depth bioinformatics sequence analysis unraveled structural features of this 34-36 kDa protein reminiscent of those observed in some capsid-associated proteins in tailed bacteriophages, with which herpesviruses are thought to share a common ancestry. This suggests that pUS10 could represent an evolutionary vestige between these two viral lineages. Using immunoaffinity purification-mass spectrometry we found that pUS10 specifically co-isolated with the inner tegument protein pUL37, which binds cytosolic capsids, contributing to initial tegumentation and eventual virion maturation. In summary, this study unveils new insights at both the system and molecular levels that can help better understand the complexity behind herpesvirus infections.
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- top 9%
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