Dataset Information

Proteome-wide analysis of human motif-domain interactions mapped on influenza a virus.

ABSTRACT: BACKGROUND:The influenza A virus (IAV) is a constant threat for humans worldwide. The understanding of motif-domain protein participation is essential to combat the pathogen. RESULTS:In this study, a data mining approach was employed to extract influenza-human Protein-Protein interactions (PPI) from VirusMentha,Virus MINT, IntAct, and Pfam databases, to mine motif-domain interactions (MDIs) stored as Regular Expressions (RegExp) in 3DID database. A total of 107 RegExp related to human MDIs were searched on 51,242 protein fragments from H1N1, H1N2, H2N2, H3N2 and H5N1 strains obtained from Virus Variation database. A total 46 MDIs were frequently mapped on the IAV proteins and shared between the different strains. IAV kept host-like MDIs that were associated with the virus survival, which could be related to essential biological process such as microtubule-based processes, regulation of cell cycle check point, regulation of replication and transcription of DNA, etc. in human cells. The amino acid motifs were searched for matches in the immune epitope database and it was found that some motifs are part of experimentally determined epitopes on IAV, implying that such interactions exist. CONCLUSION:The directed data-mining method employed could be used to identify functional motifs in other viruses for envisioning new therapies.

SUBMITTER: Garcia-Perez CA

PROVIDER: S-EPMC6019528 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Proteome-wide analysis of human motif-domain interactions mapped on influenza a virus.

García-Pérez Carlos A CA Guo Xianwu X Navarro Juan García JG Aguilar Diego Alonso Gómez DAG Lara-Ramírez Edgar E EE

BMC bioinformatics 20180625 1

<h4>Background</h4>The influenza A virus (IAV) is a constant threat for humans worldwide. The understanding of motif-domain protein participation is essential to combat the pathogen.<h4>Results</h4>In this study, a data mining approach was employed to extract influenza-human Protein-Protein interactions (PPI) from VirusMentha,Virus MINT, IntAct, and Pfam databases, to mine motif-domain interactions (MDIs) stored as Regular Expressions (RegExp) in 3DID database. A total of 107 RegExp related to h ...[more]

PMID: 29940841

Similar Datasets

Project description:BackgroundGrass carp hemorrhagic disease, caused by grass carp reovirus (GCRV), is the most fatal causative agent in grass carp aquaculture. Protein-protein interactions between virus and host are one avenue through which GCRV can trigger infection and induce disease. Experimental approaches for the detection of host-virus interactome have many inherent limitations, and studies on protein-protein interactions between GCRV and its host remain rare.ResultsIn this study, based on known motif-domain interaction information, we systematically predicted the GCRV virus-host protein interactome by using motif-domain interaction pair searching strategy. These proteins derived from different domain families and were predicted to interact with different motif patterns in GCRV. JAM-A protein was successfully predicted to interact with motifs of GCRV Sigma1-like protein, and shared the similar binding mode compared with orthoreovirus. Differentially expressed genes during GCRV infection process were extracted and mapped to our predicted interactome, the overlapped genes displayed different tissue expression distributions on the whole, the overall expression level in intestinal is higher than that of other three tissues, which may suggest that the functions of these genes are more active in intestinal. Function annotation and pathway enrichment analysis revealed that the host targets were largely involved in signaling pathway and immune pathway, such as interferon-gamma signaling pathway, VEGF signaling pathway, EGF receptor signaling pathway, B cell activation, and T cell activation.ConclusionsAlthough the predicted PPIs may contain some false positives due to limited data resource and poor research background in non-model species, the computational method still provide reasonable amount of interactions, which can be further validated by high throughput experiments. The findings of this work will contribute to the development of system biology for GCRV infectious diseases, and help guide the identification of novel receptors of GCRV in its host.

Dataset Information

Proteome-wide analysis of human motif-domain interactions mapped on influenza a virus.

Publications

Proteome-wide analysis of human motif-domain interactions mapped on influenza a virus.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets