Department of Biological Sciences, School of Science, Technology, Education, and Mathematics, University of Washington, UWBB 249, Bothell, Washington 98011-8246, USA.
Department of Microbiology, Oregon State University, 226 Nash Hall, Corvallis, Oregon 97331, USA.
Nat Microbiol. 2017 Aug 24;2:17121. doi: 10.1038/nmicrobiol.2017.121.
All animals studied to date are associated with symbiotic communities of microorganisms. These animal microbiotas often play important roles in normal physiological function and susceptibility to disease; predicting their responses to perturbation represents an essential challenge for microbiology. Most studies of microbiome dynamics test for patterns in which perturbation shifts animal microbiomes from a healthy to a dysbiotic stable state. Here, we consider a complementary alternative: that the microbiological changes induced by many perturbations are stochastic, and therefore lead to transitions from stable to unstable community states. The result is an 'Anna Karenina principle' for animal microbiomes, in which dysbiotic individuals vary more in microbial community composition than healthy individuals-paralleling Leo Tolstoy's dictum that "all happy families look alike; each unhappy family is unhappy in its own way". We argue that Anna Karenina effects are a common and important response of animal microbiomes to stressors that reduce the ability of the host or its microbiome to regulate community composition. Patterns consistent with Anna Karenina effects have been found in systems ranging from the surface of threatened corals exposed to above-average temperatures, to the lungs of patients suffering from HIV/AIDs. However, despite their apparent ubiquity, these patterns are easily missed or discarded by some common workflows, and therefore probably underreported. Now that a substantial body of research has established the existence of these patterns in diverse systems, rigorous testing, intensive time-series datasets and improved stochastic modelling will help to explore their importance for topics ranging from personalized medicine to theories of the evolution of host-microorganism symbioses.
迄今为止所研究的所有动物都与共生微生物群落有关。这些动物微生物群在正常生理功能和疾病易感性方面常常起着重要作用;预测它们对干扰的反应是微生物学的一个基本挑战。大多数微生物组动力学研究测试的模式是,干扰会将动物微生物群从健康状态转变为失调的稳定状态。在这里,我们考虑一个补充的替代方案:许多干扰引起的微生物变化是随机的,因此会导致从稳定到不稳定的群落状态的转变。其结果是动物微生物组的“安娜·卡列尼娜原则”,即失调个体的微生物群落组成比健康个体变化更大——类似于列夫·托尔斯泰的名言:“幸福的家庭都是相似的,不幸的家庭各有各的不幸”。我们认为,安娜·卡列尼娜效应是动物微生物组对减少宿主或其微生物组调节群落组成能力的应激源的常见且重要的反应。从暴露于高于平均温度的受威胁珊瑚表面到 HIV/AIDS 患者的肺部,在从系统中都发现了与安娜·卡列尼娜效应一致的模式。然而,尽管这些模式显然无处不在,但由于一些常见的工作流程很容易忽略或丢弃这些模式,因此可能报道不足。现在,大量研究已经证实了这些模式在不同系统中的存在,严格的测试、密集的时间序列数据集和改进的随机模型将有助于探索它们在从个性化医学到宿主-微生物共生进化理论等主题中的重要性。