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BMC Bioinformatics

, 18:278

Networks analysis

Abstract

BackgroundHost–pathogen interactions are important in a wide range of research fields. Given the importance of metabolic crosstalk between hosts and pathogens, a metabolic network-based reverse ecology method was proposed to infer these interactions. However, the validity of this method remains unclear because of the various explanations presented and the influence of potentially confounding factors that have thus far been neglected.

ResultsWe re-evaluated the importance of the reverse ecology method for evaluating host–pathogen interactions while statistically controlling for confounding effects using oxygen requirement, genome, metabolic network, and phylogeny data. Our data analyses showed that host–pathogen interactions were more strongly influenced by genome size, primary network parameters e.g., number of edges, oxygen requirement, and phylogeny than the reserve ecology-based measures.

ConclusionThese results indicate the limitations of the reverse ecology method; however, they do not discount the importance of adopting reverse ecology approaches altogether. Rather, we highlight the need for developing more suitable methods for inferring host–pathogen interactions and conducting more careful examinations of the relationships between metabolic networks and host–pathogen interactions.

KeywordsReverse ecology Metabolic networks Species–species interactions Systems biology AbbreviationsAICcSample size-corrected version of Akaike Information Criterion

AUCArea Under the receiver operating characteristic Curve

BSSBiosynthetic support score

BSSHMBiosynthetic support score of a host for a microbe

BSSMHBiosynthetic support score of a microbe for a host

Enumber of edges

KEGGKyoto encyclopedia of genes and genomes

MCIMetabolic complementarity index

MCIHMBiosynthetic complement index of a host for a microbe

MCIMHBiosynthetic complement index of a microbe for a host

MIPMETMIcrobial Physiology and METabolism

NNumber of nodes

PHI-basePathogen-host interactions database

Electronic supplementary materialThe online version of this article doi:10.1186-s12859-017-1696-7 contains supplementary material, which is available to authorized users.





Autor: Kazuhiro Takemoto - Kazuki Aie

Fuente: https://link.springer.com/







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