Takemoto Kazuhiro, Aie Kazuki
Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Iizuka, Fukuoka, 820-8502, Japan.
BMC Bioinformatics. 2017 May 25;18(1):278. doi: 10.1186/s12859-017-1696-7.
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.
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.
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.
宿主 - 病原体相互作用在广泛的研究领域中都很重要。鉴于宿主与病原体之间代谢串扰的重要性，有人提出了一种基于代谢网络的反向生态学方法来推断这些相互作用。然而，由于目前存在各种解释以及尚未考虑到的潜在混杂因素的影响，该方法的有效性仍不明确。
我们在使用需氧性、基因组、代谢网络和系统发育数据对混杂效应进行统计控制的同时，重新评估了反向生态学方法在评估宿主 - 病原体相互作用方面的重要性。我们的数据分析表明，与基于反向生态学的指标相比，宿主 - 病原体相互作用受基因组大小、初级网络参数（如边的数量）、需氧性和系统发育的影响更大。
这些结果表明了反向生态学方法的局限性；然而，它们并没有完全否定采用反向生态学方法的重要性。相反，我们强调需要开发更合适的方法来推断宿主 - 病原体相互作用，并更仔细地研究代谢网络与宿主 -病原体相互作用之间的关系。
