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不断增长的细菌群体在玩哪些游戏?

Which games are growing bacterial populations playing?

作者信息

Li Xiang-Yi, Pietschke Cleo, Fraune Sebastian, Altrock Philipp M, Bosch Thomas C G, Traulsen Arne

出版信息

J R Soc Interface. 2015 Jul 6;12(108):20150121. doi: 10.1098/rsif.2015.0121.

Abstract

Microbial communities display complex population dynamics, both in frequency and absolute density. Evolutionary game theory provides a natural approach to analyse and model this complexity by studying the detailed interactions among players, including competition and conflict, cooperation and coexistence. Classic evolutionary game theory models typically assume constant population size, which often does not hold for microbial populations. Here, we explicitly take into account population growth with frequency-dependent growth parameters, as observed in our experimental system. We study the in vitro population dynamics of the two commensal bacteria (Curvibacter sp. (AEP1.3) and Duganella sp. (C1.2)) that synergistically protect the metazoan host Hydra vulgaris (AEP) from fungal infection. The frequency-dependent, nonlinear growth rates observed in our experiments indicate that the interactions among bacteria in co-culture are beyond the simple case of direct competition or, equivalently, pairwise games. This is in agreement with the synergistic effect of anti-fungal activity observed in vivo. Our analysis provides new insight into the minimal degree of complexity needed to appropriately understand and predict coexistence or extinction events in this kind of microbial community dynamics. Our approach extends the understanding of microbial communities and points to novel experiments.

摘要

微生物群落无论是在频率还是绝对密度方面都呈现出复杂的种群动态。进化博弈论通过研究参与者之间的详细相互作用,包括竞争与冲突、合作与共存,为分析和模拟这种复杂性提供了一种自然的方法。经典的进化博弈论模型通常假设种群规模恒定,而这对于微生物种群来说往往并不成立。在这里,我们明确考虑了在我们的实验系统中观察到的随频率变化的生长参数的种群增长情况。我们研究了两种共生细菌(弯曲杆菌属(AEP1.3)和杜氏菌属(C1.2))的体外种群动态,它们协同保护后生动物宿主普通水螅(AEP)免受真菌感染。我们在实验中观察到的随频率变化的非线性生长速率表明,共培养中细菌之间的相互作用超出了直接竞争的简单情况,或者等效地说,超出了两两博弈的情况。这与在体内观察到的抗真菌活性的协同效应一致。我们的分析为适当理解和预测这类微生物群落动态中的共存或灭绝事件所需的最小复杂程度提供了新的见解。我们的方法扩展了对微生物群落的理解,并指出了新的实验方向。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2874/4528578/7495256c77de/rsif20150121-g1.jpg

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