Ling Yiwei, Watanabe Yu, Okuda Shujiro
Niigata University Graduate School of Medical and Dental Sciences, 1-757 Asahimachi-dori, Chuo-ku, Niigata 951-8510, Japan.
Comput Struct Biotechnol J. 2019 Jul 29;17:1040-1046. doi: 10.1016/j.csbj.2019.07.011. eCollection 2019.
Microbiome studies estimate the functions of bacterial flora in situ on the basis of species composition and gene function; however, estimation of interspecies interaction networks is challenging. This study aimed to develop a method to predict the interaction networks among bacterial species from human gut metagenome data using bioinformatics methods. Our proposed method revealed that adjacent gene pairs involved in bacterial interspecies interactions are localized at boundary regions and encode membrane proteins mediating interactions between the intracellular and extracellular environments, e.g., transporters and channel proteins, and those mediating interactions between metabolic pathways. Actual human gut metagenome data displayed numerous such highly reliable interspecies interaction gene pairs in comparison with random simulated metagenome data sets, suggesting that the species composition of the actual microbiome facilitated more robust interspecific interactions. The present results indicate that molecular interaction networks in human gut flora are organized by a combination of interaction networks common to all individuals and group-specific interaction networks.
微生物组研究基于物种组成和基因功能对原位细菌菌群的功能进行评估;然而,种间相互作用网络的评估具有挑战性。本研究旨在开发一种利用生物信息学方法从人类肠道宏基因组数据预测细菌物种间相互作用网络的方法。我们提出的方法表明,参与细菌种间相互作用的相邻基因对位于边界区域,编码介导细胞内和细胞外环境之间相互作用的膜蛋白,如转运蛋白和通道蛋白,以及介导代谢途径之间相互作用的蛋白。与随机模拟的宏基因组数据集相比,实际的人类肠道宏基因组数据显示出大量此类高度可靠的种间相互作用基因对,这表明实际微生物组的物种组成促进了更强健的种间相互作用。目前的结果表明,人类肠道菌群中的分子相互作用网络是由所有个体共有的相互作用网络和群体特异性相互作用网络组合而成的。