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微生物群落中的漂变动力学和有效群落大小。

Drift dynamics in microbial communities and the effective community size.

机构信息

School of Engineering, University of Glasgow, University Avenue, Glasgow, G12 8QQ, UK.

Department of Statistics, University of Oxford, 24-29 St Giles, Oxford, OX1 3LB, UK.

出版信息

Environ Microbiol. 2021 May;23(5):2473-2483. doi: 10.1111/1462-2920.15453. Epub 2021 Mar 23.

Abstract

The structure and diversity of all open microbial communities are shaped by individual births, deaths, speciation and immigration events; the precise timings of these events are unknowable and unpredictable. This randomness is manifest as ecological drift in the population dynamics, the importance of which has been a source of debate for decades. There are theoretical reasons to suppose that drift would be imperceptible in large microbial communities, but this is at odds with circumstantial evidence that effects can be seen even in huge, complex communities. To resolve this dichotomy we need to observe dynamics in simple systems where key parameters, like migration, birth and death rates can be directly measured. We monitored the dynamics in the abundance of two genetically modified strains of Escherichia coli, with tuneable growth characteristics, that were mixed and continually fed into 10 identical chemostats. We demonstrated that the effects of demographic (non-environmental) stochasticity are very apparent in the dynamics. However, they do not conform to the most parsimonious and commonly applied mathematical models, where each stochastic event is independent. For these simple models to reproduce the observed dynamics we need to invoke an 'effective community size', which is smaller than the census community size.

摘要

所有开放微生物群落的结构和多样性都受到个体的出生、死亡、物种形成和移民事件的影响;这些事件的确切时间是未知和不可预测的。这种随机性表现为种群动态中的生态漂变,其重要性几十年来一直是争论的根源。从理论上讲,人们认为漂变在大型微生物群落中是不可察觉的,但这与环境证据相矛盾,即即使在庞大、复杂的群落中也能看到影响。为了解决这种二分法,我们需要观察简单系统中的动态,在这些系统中,关键参数(如迁移率、出生率和死亡率)可以直接测量。我们监测了两种具有可调节生长特性的经过基因改造的大肠杆菌菌株丰度的动态,这些菌株被混合并不断输入到 10 个相同的恒化器中。我们证明了种群动态中非环境随机因素的影响非常明显。然而,它们不符合最简约和常用的数学模型,在这些模型中,每个随机事件都是独立的。为了使这些简单的模型再现观察到的动态,我们需要引入一个“有效群落大小”,它小于种群大小。

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