Computational methodology for predicting the landscape of the human–microbial interactome region level influence



Microbial communities thrive in close association among themselves and with the host, establishing protein–protein interactions (PPIs) with the latter, and thus being able to benefit (positively impact) or disturb (negatively impact) biological events in the host. Despite major collaborative efforts to sequence the Human microbiome, there is still a great lack of understanding their impact. We propose a computational methodology to predict the impact of microbial proteins in human biological events, taking into account the abundance of each microbial protein and its relation to all other microbial and human proteins. This alternative methodology is centered on an improved impact estimation algorithm that integrates PPIs between human and microbial proteins with Reactome pathway data. This methodology was applied to study the impact of 24 microbial phyla over different cellular events, within 10 different human microbiomes. The results obtained confirm findings already described in the literature and explore new ones. We believe the Human microbiome can no longer be ignored as not only is there enough evidence correlating microbiome alterations and disease states, but also the return to healthy states once these alterations are reversed.


Protein–protein interactions; host–pathogen interactions; computational prediction




Journal of bioinformatics and computational biology, Vol. 13, #05, pp. 1550023, Imperial College Press, September 2015


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Year 2016 : 2 citations

 Gomes, Francisco Isaac Fernandes, et al. "Inflammatory Cytokines Interleukin-1? and Tumour Necrosis Factor-?-Novel Biomarkers for the Detection of Periodontal Diseases: a Literature Review." Journal of Oral & Maxillofacial Research 7.2 (2016).

 Sousa, Luzia Hermínia, et al. "Effects of atorvastatin on periodontitis of rats subjected to glucocorticoid-induced osteoporosis." Journal of periodontology 87.10 (2016): 1206-1216.

Year 2015 : 3 citations

 Marques, Jéssica Raquel Cortez. In search of the molecular profile characteristic of attention deficit hyperactivity disorder and of dyslexia. MS thesis. Universidade de Aveiro, 2015.

 Serra, Beatriz Patrício. Identificação de biomarcadores salivares de doença periodontal em pacientes com gengivite. Diss. 2015.

 Hortênsio, Andreia Soraia Pinto. Identificação de biomarcadores salivares de doença periodontal em pacientes com diabetes mellitus tipo 2. Diss. 2015.