Limitations of a Metabolic Network-based Reverse Ecology Method for Inferring Host-pathogen Interactions

Overview

Journal BMC Bioinformatics

Publisher Biomed Central

Specialty Biology

Date 2017 May 27

PMID 28545448

Citations 2

Authors

Kazuhiro Takemoto

Kazuki Aie

Affiliations

Soon will be listed here.

Abstract

Background: Host-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.

Results: We 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.

Conclusion: These 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.

Citing Articles

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Are dominant plant species more susceptible to leaf-mining insects? A case study at Saihanwula Nature Reserve, China.

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