Synthetic microbiota reveal priority effects and keystone strains in the Arabidopsis phyllosphere

Abstract

Multicellular organisms, including plants, are colonized by microorganisms, some of which are beneficial to growth and health. The assembly rules for establishing plant microbiota are not well understood, and neither is the extent to which their members interact. We conducted drop-out and late introduction experiments by inoculating Arabidopsis thaliana with synthetic communities from a resource of 62 native bacterial strains to test how arrival order shapes community structure. As a read-out we tracked the relative abundance of all strains in the phyllosphere of individual plants. Our results showed that community assembly is historically contingent and subject to priority effects. Missing strains could, to various degrees, invade an already established microbiota, which was itself resistant and remained largely unaffected by latecomers. Additionally, our results indicate that individual strains of Proteobacteria (Sphingomonas, Rhizobium) and Actinobacteria (Microbacterium, Rhodococcus) have the greatest potential to affect community structure as keystone species.

Fig. 1. Concept of Drop-Out and Late Introduction Experiments Using Synthetic Microbiota

a) For the control community, axenic plants are inoculated with a 62-strain synthetic microbiota and 16S rRNA gene amplicon sequencing is used as a read-out for relative abundance. b) In order to understand how a particular group or strain ("A", "B", "C", or "D") affects other groups/strains, one group ("A") is removed to analyse the effects of its absence on the rest of the community. Subsequently, this group is introduced later in order to evaluate the extent to which late-arriving strains can invade a pre-established microbiota as well as the overall effects of arrival order on community assembly.

Fig. 2. Relative Abundance in Control Community

Relative abundance of the 62-strain control community (t₁ and t₂ combined, n = 48, 1 independent replicate). Violin plot with swarm plot overlay and pie chart are coloured by strain phylogeny. For each strain, the horizontal line represents the median and points represent individual samples. Along the bottom, the number of replicates where a given strain was not detected are indicated by circle size and count.

Fig. 3. Proteobacteria Class Drop-Out and Late Introduction Experiment

a) Schematic of drop-out and late introduction experiments showing the various analysed comparisons ("I", "II", and "III") among the control, the late arrival, and the group absent communities (n = 15-24 per condition; 1 independent replicate). b) Overall effects of class drop-outs and late introduction (PERMANOVA). Rows are labeled with the test groups being compared according to panel (a). Circle size and shade represent effect size and stars denote significance. c) Strains affected by class drop-outs and late introductions (DESeq2). Column labels refer to the test groups being compared according to panel (a) for each drop-out/ late introduction condition. For mock spray control, see Supp Fig. 2b. Strains are phylogenetically clustered and heatmap colours represent the log₂ fold change of the test condition/control community. p-values (Benjamini-Hochberg corrected): * = 0.05, ** = 0.01, *** = 0.001, and **** = 0.0001.

Fig. 4. Single Strain Drop-Outs

a) Overall effects of single strain drop-outs (PERMANOVA). Data from two independent replicates (n = 11-12 per condition per replicate) was analysed separately and together. Strains are phylogenetically clustered and coloured. Circle size and shade represent effect size and stars denote significance. p-values (Benjamini-Hochberg corrected): * = 0.05, ** = 0.01, *** = 0.001, and **** = 0.0001. b) Exemplary PCA plots of the L203-Microbacterium, L231-Sphingomonas, L233-Rhodococcus, and L262-Rhizobium drop-outs generated from the two independent replicates as well as from the combined dataset. R1: replicate 1, R2: replicate 2. c) Strains affected by the single strain drop-outs (p ≤ 0.01). Effector strains (left side) and affected strains (right side) are clustered and coloured by phylogeny. Blue lines and red lines represent negative and positive effects, respectively, inferred from the single strain drop-out experiments. Line thickness correlates linearly with fold changes.

Fig. 5. Causal network (p ≤ 0.01) based on single-strain drop-outs.

Nodes (strains) are coloured by phylogeny and labels refer to strain names. Rectangles represent effector strains that were individually removed, while ovals are strains that were affected by various drop-outs. Red and blue arrows (depicting positive and negative effects, respectively) represent edges (direct or indirect interactions).

Fig. 6. Correlation between node out degree and effect size upon node removal

Pearson correlation (r = 0.904, p = 5.8 x 10^-10) between node out degree and effect size upon node removal. Labels refer to strain names. See Fig. 2 or Supplementary Table 2 for strain names and phylogeny.