微生物群
压力源
生物
进化生物学
疾病
生态学
遗传学
医学
神经科学
病理
作者
Jesse Zaneveld,Ryan McMinds,Rebecca Vega Thurber
标识
DOI:10.1038/nmicrobiol.2017.121
摘要
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. This Perspective argues that Anna Karenina effects (that is, changes resulting in increased variation in community composition under stress) are a common and important response of animal microbiomes that have been under-reported.
科研通智能强力驱动
Strongly Powered by AbleSci AI