Functional Microbial Features Driving Community Assembly During Seed Germination and Emergence

Abstract

Microbial interactions occurring on and around seeds are especially important for plant fitness since seed-borne microorganisms are the initial source of inoculum for the plant microbiota. In this study, we analyze structural and functional changes occurring within the plant microbiota at these early stages of the plant cycle, namely germination and emergence. To this purpose, we performed shotgun DNA sequencing of microbial assemblages associated to seeds, germinating seeds and seedlings of two plant species: bean and radish. We observed an enrichment of Enterobacteriales and Pseudomonadales during emergence and a set of functional traits linked to copiotrophy that could be responsible for this selection as a result of an increase of nutrient availability after germination. Representative bacterial isolates of taxa that are selected in seedlings showed indeed faster bacterial growth rate in comparison to seed-associated bacteria isolates. Finally, binning of metagenomics contigs results in the reconstruction of population genomes of the major bacterial taxa associated to the samples. Together, our results demonstrate that, although seed microbiota varied across plant species, nutrient availability during germination elicits changes of the composition of microbial communities by potentially selecting microbial groups with functional traits linked to copiotrophy. The data presented here represents the first attempts to empirically assess changes in the microbial community during plant emergence and moves us toward a more holistic understanding of the plant microbiome.

Keywords: copiotrophy; metagenomics; plant microbial communities; seed germination; seed microbiome.

FIGURE 1

Structure and composition of microbial assemblages associated to seeds, germinating seeds and seedlings. (A) Phylogenetic assignment of reads in bacterial classes was performed with Clark, a k-mer based approach. (B) Changes in microbial richness (left panels) and diversity (right panels) among the samples investigated. Letters indicate differences between individual means as assessed with one factor ANOVA with post hoc Tukey HSD (P < 0.01). (C) PCoA plots based on Bray–Curtis index calculated at the genus level. (D) Abundant bacterial genus in the samples investigated. Asterisks (^∗) indicate taxa that are significantly more abundant in seedling samples in comparison to seeds (DeSeq2; log2 FC > 3, P < 0.01). S, seeds; G, germinating seeds and P: Seedlings.

FIGURE 2

Functional composition of microbial assemblages associated to seeds, germinating seeds and seedlings. (A) Relative abundance of COGs functional categories in the predicted proteomes of the samples investigated. (B) Changes in COGs richness (left panels) and diversity (right panels) among the samples investigated. Letters indicate differences between individual means as assessed with one factor ANOVA with post hoc Tukey HSD (P < 0.01). (C) PCoA plots based on Bray-Curtis index calculated on COGs table. (D) Abundant functional categories in the samples investigated. Of note is that the functional categories S (function unknown) and R (general functional prediction only) were not reported in this panel. Asterisks (^∗) indicate taxa that are significantly more abundant in seedling samples in comparison to seeds [ANOVA with post hoc Tukey HSD (P < 0.05)].

FIGURE 3

Analysis of some of the key copiotrophic characteristics in metagenome datasets. (A) rrn copy number of taxa that are significantly more or less abundant in seedling samples in comparison to seeds (DeSeq2; log2 FC > 3, P < 0.01). (B) Average genome size and (C) Proportion of classified reads among the samples investigated. Letters indicate differences between individual means assessed with one factor ANOVA with post hoc Tukey HSD (P < 0.05). The left part of the panel shows bean samples and the right part radish samples. S, seeds; G, germinating seeds, and P, Seedlings.

FIGURE 4

Quantification of seed-associated bacteria potential growth on bean and radish seed exudates. (A) Metagenomics reads relative abundance Log2fold change in seedlings in comparison to seeds of the nine selected taxa according to DeSeq2. (B) Area under the growth curve (optical density [OD] in time) as a marker of the potential growth of the different bacteria strains. Letters indicate differences between individual means assessed with one factor ANOVA with post hoc Tukey HSD (P < 0.05).

FIGURE 5

Circle packing visualization of ANIb values. MAGs (black circles) and closely related genome sequences (colors circles) have been clustered according to their ANIb values. Inner and outer circles represent ANIb values at a cutoff of 0.65, 0.90 and 0.95 respectively. Although, Acinetobacter belong to the Pseudomonadales order, the ANIb cut-off chosen placed the genus outside this order. A total of 10 MAGs could be considered as new bacterial cliques.