ABSTRACT

How the gut microbiota is organized across space is postulated to influence microbial succession and its mutualistic relationships with the host. The lack of dynamic or perturbed abundance data poses considerable challenges for characterizing the spatial pattern of microbial interactions. We integrate allometric scaling theory, evolutionary game theory, and prey-predator theory into a unified framework under which quasi-dynamic microbial networks can be inferred from static abundance data. We illustrate that such networks can capture the full properties of microbial interactions, including causality, the sign of the causality, strength, and feedback loop, and are dynamically adaptive along spatial gradients, and context-specific, characterizing variability between individuals and within the same individual across time and space. We design and conduct a gut microbiota study to validate the model, characterizing key spatial determinants of the microbial differences between ulcerative colitis and healthy controls. Our model provides a sophisticated means of unraveling a complete atlas of how microbial interactions vary across space and quantifying causal relationships between such spatial variability and change in health state.

摘要

假设肠道微生物群在空间中的组织方式会影响微生物的演替及其与宿主的共生关系。缺乏动态或扰动的丰度数据对表征微生物相互作用的空间模式提出了相当大的挑战。我们将异速生长尺度理论、进化博弈论和捕食者理论整合到一个统一的框架中，在该框架下，可以从静态丰度数据中推断出准动态微生物网络。我们说明这样的网络可以捕捉微生物相互作用的全部特性，包括因果关系、因果关系的符号、强度和反馈回路，并且可以沿空间梯度动态自适应，并且特定于上下文，表征个体之间和同一个体之间的变异性跨越时空的个体。我们设计并进行了一项肠道微生物群研究以验证该模型，表征溃疡性结肠炎和健康对照之间微生物差异的关键空间决定因素。我们的模型提供了一种复杂的方法来解开微生物相互作用如何在空间中变化的完整图谱，并量化这种空间变异性与健康状态变化之间的因果关系。