In natural environments, plants are exposed to diverse microbiota that they interact with in complex ways. While plant–pathogen interactions have been intensely studied to understand defense mechanisms in plants, many microbes and microbial communities can have substantial beneficial effects on their plant host. Such beneficial effects include improved acquisition of nutrients, accelerated growth, resilience against pathogens, and improved resistance against abiotic stress conditions such as heat, drought, and salinity. However, the beneficial effects of bacterial strains or consortia on their host are often cultivar and species specific, posing an obstacle to their general application. Remarkably, many of the signals that trigger plant immune responses are molecularly highly similar and often identical in pathogenic and beneficial microbes. Thus, it is unclear what determines the outcome of a particular microbe–host interaction and which factors enable plants to distinguish beneficials from pathogens. To unravel the complex network of genetic, microbial, and metabolic interactions, including the signaling events mediating microbe–host interactions, comprehensive quantitative systems biology approaches will be needed.

在自然环境中，植物暴露于多种微生物，它们以复杂的方式相互作用。尽管已经深入研究了植物与病原体之间的相互作用，以了解植物的防御机制，但许多微生物和微生物群落对其植物宿主可能产生实质性的有益影响。这样的有益效果包括改善营养获取，加速生长，抵抗病原体以及改善对非生物胁迫条件（如高温，干旱和盐度）的抵抗力。然而，细菌菌株或菌群对其宿主的有益作用通常是栽培品种和物种特异性的，这阻碍了它们的普遍应用。值得注意的是，许多触发植物免疫反应的信号在病原微生物和有益微生物中在分子上高度相似，并且通常相同。因此，目前尚不清楚什么决定了特定微生物与宿主之间的相互作用的结果，以及哪些因素使植物能够将有益物质与病原体区分开来。为了弄清遗传，微生物和代谢相互作用的复杂网络，包括介导微生物与宿主相互作用的信号事件，将需要全面的定量系统生物学方法。