Bacterial social interactions drive the emergence of differential spatial colony structures.
Bacterial social interactions drive the emergence of differential spatial colony structures.
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DOI：
10.1186/s12918-015-0188-5
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发表时间：
2015-09-16
影响因子：
--
通讯作者：
Lu T
中科院分区：
文献类型：
--
作者：
Blanchard AE;Lu T
社会相互作用已越来越多地被认为是影响细菌群落动态和功能的主要因素之一。要了解他们的功能作用，使强大的合成财团的设计，一个基本步骤是确定个人的社会互动和社区的时空结构之间的关系。我们提出了一个系统的计算调查，这种关系的两个物种的社区开发和利用混合计算框架，结合离散元技术与反应扩散方程。我们发现，有害的相互作用会导致相对丰度的方差增加，存活谱系急剧减少，以及粗糙的扩展前沿。相反，有益的相互作用有助于减少相对丰度的变化，增加谱系数，以及平滑的扩展前沿。我们还发现，互惠促进空间同质性和种群鲁棒性，而竞争增加空间隔离和种群波动。为了检验这些发现的一般性，测试和分析了大量具有不同密度和物种丰度的初始条件。此外，还建立了一个简化的数学模型，对研究结果进行了分析解释。这项工作推进了我们对细菌社会相互作用和种群结构的基本理解，同时有利于合成生物学促进人工微生物财团的工程。本文的在线版本（doi：10.1186/s12918-015-0188-5）包含补充材料，可供授权用户使用。
Social interactions have been increasingly recognized as one of the major factors that contribute to the dynamics and function of bacterial communities. To understand their functional roles and enable the design of robust synthetic consortia, one fundamental step is to determine the relationship between the social interactions of individuals and the spatiotemporal structures of communities. We present a systematic computational survey on this relationship for two-species communities by developing and utilizing a hybrid computational framework that combines discrete element techniques with reaction-diffusion equations. We found that deleterious interactions cause an increased variance in relative abundance, a drastic decrease in surviving lineages, and a rough expanding front. In contrast, beneficial interactions contribute to a reduced variance in relative abundance, an enhancement in lineage number, and a smooth expanding front. We also found that mutualism promotes spatial homogeneity and population robustness while competition increases spatial segregation and population fluctuations. To examine the generality of these findings, a large set of initial conditions with varying density and species abundance was tested and analyzed. In addition, a simplified mathematical model was developed to provide an analytical interpretation of the findings. This work advances our fundamental understanding of bacterial social interactions and population structures and, simultaneously, benefits synthetic biology for facilitated engineering of artificial microbial consortia. The online version of this article (doi:10.1186/s12918-015-0188-5) contains supplementary material, which is available to authorized users.