Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.
Department of Pediatrics, University of California, San Diego, CA, USA.
Nat Microbiol. 2019 Aug;4(8):1253-1267. doi: 10.1038/s41564-019-0491-9. Epub 2019 Jul 23.
Advances in metagenome sequencing of the human microbiome have provided a plethora of new insights and revealed a close association of this complex ecosystem with a range of human diseases. However, there is little knowledge about how the different members of the microbial community interact with each other and with the host, and we lack basic mechanistic understanding of these interactions related to health and disease. Mathematical modelling has been demonstrated to be highly advantageous for gaining insights into the dynamics and interactions of complex systems and in recent years, several modelling approaches have been proposed to enhance our understanding of the microbiome. Here, we review the latest developments and current approaches, and highlight how different modelling strategies have been applied to unravel the highly dynamic nature of the human microbiome. Furthermore, we discuss present limitations of different modelling strategies and provide a perspective of how modelling can advance understanding and offer new treatment routes to impact human health.
宏基因组测序技术在人类微生物组学中的进展提供了大量新的见解，并揭示了这个复杂生态系统与一系列人类疾病的密切关联。然而，我们对微生物群落的不同成员如何相互作用以及与宿主相互作用知之甚少，并且我们缺乏与健康和疾病相关的这些相互作用的基本机制理解。数学建模已被证明对于深入了解复杂系统的动态和相互作用非常有利，近年来，已经提出了几种建模方法来增强我们对微生物组的理解。在这里，我们回顾了最新的发展和当前的方法，并强调了不同的建模策略如何应用于揭示人类微生物组的高度动态性质。此外，我们讨论了不同建模策略的当前局限性，并提供了一个视角，说明建模如何促进理解并提供新的治疗途径来影响人类健康。
