Limitations of a metabolic network-based reverse ecology method for inferring host–pathogen interactions

BMC Bioinformatics

Research Article

Kazuhiro Takemoto¹  Kazuki Aie¹ 

[1] Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, 820-8502, Iizuka, Fukuoka, Japan;

关键词: Reverse ecology;    Metabolic networks;    Species–species interactions;    Systems biology;   

DOI  :  10.1186/s12859-017-1696-7

 received in 2017-02-13, accepted in 2017-05-18,  发布年份 2017

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY   
© The Author(s). 2017