Successive passaging of a plant-associated microbiome reveals robust habitat and host genotype-dependent selection

Abstract

There is increasing interest in the plant microbiome as it relates to both plant health and agricultural sustainability. One key unanswered question is whether we can select for a plant microbiome that is robust after colonization of target hosts. We used a successive passaging experiment to address this question by selecting upon the tomato phyllosphere microbiome. Beginning with a diverse microbial community generated from field-grown tomato plants, we inoculated replicate plants across 5 plant genotypes for 4 45-d passages, sequencing the microbial community at each passage. We observed consistent shifts in both the bacterial (16S amplicon sequencing) and fungal (internal transcribed spacer region amplicon sequencing) communities across replicate lines over time, as well as a general loss of diversity over the course of the experiment, suggesting that much of the naturally observed microbial community in the phyllosphere is likely transient or poorly adapted within the experimental setting. We found that both host genotype and environment shape microbial composition, but the relative importance of genotype declines through time. Furthermore, using a community coalescence experiment, we found that the bacterial community from the end of the experiment was robust to invasion by the starting bacterial community. These results highlight that selecting for a stable microbiome that is well adapted to a particular host environment is indeed possible, emphasizing the great potential of this approach in agriculture and beyond. In light of the consistent response of the microbiome to selection in the absence of reciprocal host evolution (coevolution) described here, future studies should address how such adaptation influences host health.

Keywords: experimental evolution; microbiome assembly; microbiome engineering; microbiome selection; phyllosphere.

Fig. 1.

Serial passaging of the phyllosphere microbiome. (A) Experimental design of serial passaging experiment in which microbial inoculum from an agricultural tomato field was inoculated onto replicates of 5 genotypes and passaged for 4 passages. (B) Plants were first inoculated when they were ∼2.5 wk old, and the entire plant was sampled at ∼9 wk old. (C) Bacterial abundance was measured at the end of each passage from experimental (Exp.) and control plants by using ddPCR and normalized to the weight of each plant. Inoculum density was calculated as well. Note that our measures of bacterial growth likely overestimate the starting densities and do not account for population turnover (as a result of cell death and replacement within a passage) and are therefore highly conservative.

Fig. 2.

Bacterial community change over time. (A) Principal coordinates analysis (PCoA) plot of Bray–Curtis dissimilarity among samples shows a significant effect of genotype in P1 and P2 (determined by PERMANOVA tests). Ellipses indicate 95% confidence around the clustering. (B) The percent of original inoculum OTUs present at each passage was calculated (green diamonds), and the reads/sample of inoculum OTUs out of total reads was calculated for each plant at every passage and displayed on a box plot. (C and D) Plots of richness (C) and Shannon’s alpha diversity index (D) at each passage show a significant decrease over time. (E) Bray–Curtis dissimilarities between microbiomes in P1 were compared to those in P1, P2, P3, and P4, and linear and quadratic models were fit to the data. Corrected P values for multiple pairwise comparisons in C and D are indicated on the graph. *P ≤ 0.05; ***P ≤ 0.001.

Fig. 3.

Changing relative abundance of top 100 OTUs. A heat map showing relative abundance of the top 100 OTUs illustrates the changing community composition at multiple taxonomic levels. Full taxonomy of OTUs is found in SI Appendix, Table S1. Inoc, inoculum.

Fig. 4.

Occupancy–abundance curves. For each OTU, its occupancy (or proportion of plant hosts in which it was found) is plotted against the log(10) of its relative abundance. OTUs belonging to a phylum other than those in the top 4 phyla are classified as “other.” (A) P1. (B) P2. (C) P3. (D) P4.

Fig. 5.

Testing microbiome adaptation. (A) Plants were inoculated with pooled, passaged microbiomes from the end of P1, P4, or a 50:50 mix of the 2. (B) Bacterial abundance was measured by using ddPCR. (C) A PCoA plot of Bray–Curtis dissimilarity (colored by inoculum source) shows that P1 plants have bacterial communities that are significantly different from P4 and Mixed plants, which are indistinguishable. (D) Shannon’s alpha diversity of the inoculum and experimental plants show significant differences between samples. (E) A bar graph illustrating composition of the top 10 OTUs shows differences in taxa among both the inoculum and experimental plants. Corrected P values for multiple pairwise comparisons in D are indicated on the graph. *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001. Mix, Mixed.