Investigation and functional enrichment analysis of the human host interaction network with common gram-negative respiratory pathogens predicts possible association with lung adenocarcinoma

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Abstract

Haemophilus influenzae (Hi), Moraxella catarrhalis (MorCa) and Pseudomonas aeruginosa (Psa) are three of the most common gram-negative bacteria responsible for human respiratory diseases. In this study, we aimed to identify, using the functional enrichment analysis (FEA), the human gene interaction network with the aforementioned bacteria in order to elucidate the full spectrum of induced pathogenicity. The Human Pathogen Interaction Database (HPIDB 3.0) was used to identify the human proteins that interact with the three pathogens. FEA was performed via the ToppFun tool of the ToppGene Suite and the GeneCodis database so as to identify enriched gene ontologies (GO) of biological processes (BP), cellular components (CC) and diseases. In total, 11 human proteins were found to interact with the bacterial pathogens. FEA of BP GOs revealed associations with mitochondrial membrane permeability relative to apoptotic pathways. FEA of CC GOs revealed associations with focal adhesion, cell junctions and exosomes. The most significantly enriched annotations in diseases and pathways were lung adenocarcinoma and cell cycle, respectively. Our results suggest that the Hi, MorCa and Psa pathogens could be related to the pathogenesis and/or progression of lung adenocarcinoma via the targeting of the epithelial cellular junctions and the subsequent deregulation of the cell adhesion and apoptotic pathways. These hypotheses should be experimentally validated.

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Giannakou, L. E., Giannopoulos, A. S., Hatzoglou, C., Gourgoulianis, K. I., Rouka, E., & Zarogiannis, S. G. (2021). Investigation and functional enrichment analysis of the human host interaction network with common gram-negative respiratory pathogens predicts possible association with lung adenocarcinoma. Pathophysiology, 28(1), 20–33. https://doi.org/10.3390/pathophysiology28010003

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