Determining causal links between interaction type and network structure in microbial communities

生态群落作为相互作用的物种网络而存在，这些网络的结构决定了它们的稳定性和功能。观察性研究表明，网络结构取决于物种之间的相互作用主要是互利共生还是对抗，但这种关系的因果关系仍不清楚。在这里，我们将使用细菌群落及其共生质粒来通过实验确定相互作用类型（互惠与拮抗）如何影响群落网络结构。我们的系统非常适合解决这些问题，因为细菌-质粒相互作用可以通过简单的环境操作（添加质粒赋予抗性的抗生素）从对抗性转变为共生性，并且可以在几周内观察到群落网络结构的变化。该项目的大规模实施是通过应用一种新型的免培养方法 EpiPCR 来实现的，该方法可以对细菌-质粒关联进行高通量评估。生态稳定性的预测作用以及支撑相互作用类型网络结构关系的新型生态进化机制将通过表型和遗传实验的结合以及理论的补充来评估。

Ecological communities exist as networks of interacting species, and the structure of these networks determine their stability and function. Observational studies suggest that network structure depends upon whether interactions between species are predominantly mutualistic or antagonistic, however the causality of this relationship remains unclear. Here, we will use communities of bacteria and their symbiotic plasmids to experimentally determine how interaction type (mutualistic versus antagonistic) affects community network structure. Our system is ideal to address these questions because bacteria-plasmid interactions can be switched from antagonistic to mutualistic through simple environmental manipulations (the addition of antibiotics to which the plasmids confer resistance), and changes in community network structure can be observed over a matter of weeks. The large-scale of this project is made possible by the application of a novel culture-free method, epicPCR, which allows high-throughput assessment of bacteria-plasmid associations. The predicted role of ecological stability, as well as novel eco-evolutionary mechanisms, underpinning the interaction type-network structure relationships will be assessed by a combination of phenotypic and genetic experiments complemented by theory.