An integrative method to unravel the host-parasite interactome: an orthology-based approach

Abstract

The study of molecular host-parasite interactions is essential to understand parasitic infection and adaptation within the host system. As well, prevention and treatment of infectious diseases require clear understanding of the molecular crosstalk between parasites and their hosts. As yet, experimental large-scale identification of host-parasite molecular interactions remains challenging and the use of in silico predictions becomes then necessary. Here, we propose a computational integrative approach to predict host-parasite protein-protein interaction (PPI) networks resulting from the infection of human by 12 different parasites. We used an orthology-based method to transfer high-confidence intraspecies interactions obtained from the STRING database to the corresponding inter-species protein pairs in the host-parasite system. To reduce the number of spurious predictions, our approach uses either the parasites predicted secretome and membrane proteins or only the secretome depending on whether they are uni-or multicellular respectively. Besides, the host proteome is filtered for proteins expressed in selected cellular localizations and tissues supporting the parasites growth. We evaluated the inferred interactions by analyzing the enriched biological processes and pathways in the predicted networks and their association to known parasitic invasion and evasion mechanisms. The resulting PPI networks were compared across parasites to identify common mechanisms that may define a global pathogenic hallmark. The predicted PPI networks can be visualized and downloaded at http://orthohpi.jensenlab.org. Author SummaryA protein-protein interaction (PPI) network is a collection of interactions between proteins from one or more organisms. Host-parasite PPIs are key to understanding the biology of different parasitic diseases, since predicting PPIs enable to know more about the parasite invasion, infection and persist. Our understanding of PPIs between host and parasites is still . CC-BY 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/147868 doi: bioRxiv preprint first posted online 3 very limited, as no many systematic experimental studies have so far been performed.Efficacy of treatments for parasitic diseases is limited and in many cases parasites evolve resistance. Thus, there is an urgent need to develop novel drugs or vaccines for these neglected diseases, and thus interest in the functions and interactions of proteins associated with parasitism processes. Here we developed an in silico method to shed light on the interactome in twelve human parasites by combining an orthology based strategy and integrating, domain-domain interaction data, sub-cellular localization and to give a spatial context, we only took in to account those human tissues that support the parasite´s tropism.Here we show that is possible to identify relevant interactions across different parasites and their human h...

Network analysis of host-pathogen protein interactions in microbe induced cardiovascular diseases

“…All the experimentally determined HP-PPIs related to the human host and all pathogens were gathered, housed in several HPI databases: Reactome [ 52 ], HMDAD [ 53 ], PHI-base [ 54 ], OrthoHPI [ 55 ], VirusMINT [ 56 ], MatrixDB [ 57 ], BioGrid [ 58 ], HPIDb [ 59 ], MINT [ 60 ], IMEx [ 61 ], IntAct [ 62 ], UniProt [ 63 ], MPIDB [ 64 ], VirHostNet [ 65 ], I2D [ 66 ], InnateDB [ 67 ], DIP [ 68 ] and PHISTO [ 69 ]. These databases are exclusively dedicated for HPIs, however, there are some other databases that serve as data repositories to search and collect protein/gene interaction data, provide the information of PPIs of a single host [ 70 ].…”

“…All the experimentally determined HP-PPIs related to the human host and all pathogens were gathered, housed in several HPI databases: Reactome [52], HMDAD [53], PHI-base [54], OrthoHPI [55], VirusMINT [56], MatrixDB [57], BioGrid [58], HPIDb [59], MINT [60], IMEx [61], IntAct [62], UniProt [63], MPIDB [64], VirHostNet [65], I2D [66], InnateDB [67], DIP [68] and PHISTO [69].…”