Whose microbiome is it? : adaptive interactions of keystone species in plant microbiomes

Plant organs are colonized by diverse microbial organisms that help the plant to ensure fitness and survival in unpredictable environments. Different factors shape the microbiome of plants including the plant genotype, environmental conditions and microbe-microbe interactions. Certain highly interactive microbes were identified as keystone species in plant-associated microbial communities, i.e. species that are important for the structure and integrity of a community, regardless of its abundance in the ecosystem. Keystones in plant microbiomes could be important in structuring early colonization of plants by microorganisms and in controlling the variability of plant-associated microbiomes. The goal of this project was to evaluate the hypothesis that the plant microbiome is a combination of the microbiomes of the host and its keystones, focusing on early colonization. In this work a new amplicon sequencing pipeline was developed to investigate the leaf microbiomes of nine wild Arabidopsis thaliana population identified in Jena, Germany. We found, that their core microbiome is largely, but not completely shared with other co-habituating ground-dwelling ruderal plant species. The difference between A. thaliana bacteriomes and those of other plants depended on how variable bacteriomes were in each population, which changed between years in each population. We then tested the importance of early microbial colonization in two of the wild A. thaliana populations and one A. thaliana reference strain and identified efficient early colonizers as possible keystone species. We found, that if they influenced microbial community assembly they increased the variation of bacterial communities rather than decreasing it. To summarize, early colonizing bacteria affect the outcome of plant-to-plant variation. We hypothesize that these are bacterial keystone species that do not shape the plants microbiome in a specific way, but rather serve as cues leading to more variability.