Dai Die, Wang Teng, Wu Sicheng, Gao Na L, Chen Wei-Hua
Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-Imaging, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
College of Life Science, Henan Normal University, Xinxiang, China.
Front Microbiol. 2019 Jun 4;10:1205. doi: 10.3389/fmicb.2019.01205. eCollection 2019.
In recent decades, increasing evidence has strongly suggested that gut microbiota play an important role in many intestinal diseases including inflammatory bowel disease (IBD) and colorectal cancer (CRC). The composition of gut microbiota is thought to be largely shaped by interspecies competition for available resources and also by cooperative interactions. However, to what extent the changes could be attributed to external factors such as diet of choice and internal factors including mutual relationships among gut microbiota, respectively, are yet to be elucidated. Due to the advances of high-throughput sequencing technologies, flood of (meta)-genome sequence information and high-throughput biological data are available for gut microbiota and their association with intestinal diseases, making it easier to gain understanding of microbial physiology at the systems level. In addition, the newly developed genome-scale metabolic models that cover significant proportion of known gut microbes enable researchers to analyze and simulate the system-level metabolic response in response to different stimuli in the gut, providing deeper biological insights. Using metabolic interaction network based on pair-wise metabolic dependencies, we found the same interaction pattern in two IBD datasets and one CRC datasets. We report here for the first time that the growth of significantly enriched bacteria in IBD and CRC patients could be boosted by other bacteria including other significantly increased ones. Conversely, the growth of probiotics could be strongly inhibited from other species, including other probiotics. Therefore, it is very important to take the mutual interaction of probiotics into consideration when developing probiotics or "microbial based therapies." Together, our metabolic interaction network analysis can predict majority of the changes in terms of the changed directions in the gut microbiota during enteropathogenesis. Our results thus revealed unappreciated interaction patterns between species could underlie alterations in gut microbiota during enteropathogenesis, and between probiotics and other microbes. Our methods provided a new framework for studying interactions in gut microbiome and their roles in health and disease.
近几十年来,越来越多的证据有力地表明,肠道微生物群在许多肠道疾病中发挥着重要作用,包括炎症性肠病(IBD)和结直肠癌(CRC)。肠道微生物群的组成被认为在很大程度上是由对可用资源的种间竞争以及合作相互作用所塑造的。然而,这些变化分别在多大程度上可归因于外部因素(如饮食选择)和内部因素(包括肠道微生物群之间的相互关系),仍有待阐明。由于高通量测序技术的进步,大量的(宏)基因组序列信息和高通量生物学数据可用于肠道微生物群及其与肠道疾病的关联,这使得在系统层面更容易了解微生物生理学。此外,新开发的覆盖了相当比例已知肠道微生物的基因组规模代谢模型,使研究人员能够分析和模拟肠道对不同刺激的系统层面代谢反应,提供更深入的生物学见解。利用基于成对代谢依赖性的代谢相互作用网络,我们在两个IBD数据集和一个CRC数据集中发现了相同的相互作用模式。我们首次在此报告,IBD和CRC患者中显著富集的细菌的生长可被包括其他显著增加的细菌在内的其他细菌促进。相反,益生菌的生长可能会受到其他物种(包括其他益生菌)的强烈抑制。因此,在开发益生菌或“基于微生物的疗法”时,考虑益生菌的相互作用非常重要。总之,我们的代谢相互作用网络分析可以预测肠道发病过程中肠道微生物群变化方向方面的大多数变化。因此,我们的结果揭示了未被认识到的物种间相互作用模式可能是肠道发病过程中肠道微生物群变化以及益生菌与其他微生物之间相互作用的基础。我们的方法为研究肠道微生物组中的相互作用及其在健康和疾病中的作用提供了一个新框架。
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