Bauer Eugen, Thiele Ines
Luxembourg Centre for Systems Biomedicine, Universite du Luxembourg, Esch-sur-Alzette, Luxembourg.
mSystems. 2018 Mar 27;3(3). doi: 10.1128/mSystems.00209-17. eCollection 2018 May-Jun.
An important hallmark of the human gut microbiota is its species diversity and complexity. Various diseases have been associated with a decreased diversity leading to reduced metabolic functionalities. Common approaches to investigate the human microbiota include high-throughput sequencing with subsequent correlative analyses. However, to understand the ecology of the human gut microbiota and consequently design novel treatments for diseases, it is important to represent the different interactions between microbes with their associated metabolites. Computational systems biology approaches can give further mechanistic insights by constructing data- or knowledge-driven networks that represent microbe interactions. In this minireview, we will discuss current approaches in systems biology to analyze the human gut microbiota, with a particular focus on constraint-based modeling. We will discuss various community modeling techniques with their advantages and differences, as well as their application to predict the metabolic mechanisms of intestinal microbial communities. Finally, we will discuss future perspectives and current challenges of simulating realistic and comprehensive models of the human gut microbiota.
人类肠道微生物群的一个重要标志是其物种多样性和复杂性。多种疾病都与多样性降低有关，进而导致代谢功能减少。研究人类微生物群的常用方法包括高通量测序及后续的相关分析。然而，为了理解人类肠道微生物群的生态，并因此设计出针对疾病的新疗法，呈现微生物与其相关代谢物之间的不同相互作用非常重要。计算系统生物学方法可以通过构建代表微生物相互作用的数据驱动或知识驱动网络，提供进一步的机制性见解。在这篇小型综述中，我们将讨论系统生物学中用于分析人类肠道微生物群的当前方法，特别关注基于约束的建模。我们将讨论各种群落建模技术及其优缺点，以及它们在预测肠道微生物群落代谢机制方面的应用。最后，我们将讨论模拟真实且全面的人类肠道微生物群模型的未来前景和当前挑战。
