Structural variability and niche differentiation in the rhizosphere and endosphere bacterial microbiome of field-grown poplar trees

Abstract

Background: The plant microbiome represents one of the key determinants of plant health and productivity by providing a plethora of functional capacities such as access to low-abundance nutrients, suppression of phytopathogens, and resistance to biotic and/or abiotic stressors. However, a robust understanding of the structural composition of the bacterial microbiome present in different plant microenvironments and especially the relationship between below-ground and above-ground communities has remained elusive. In this work, we addressed hypotheses regarding microbiome niche differentiation and structural stability of the bacterial communities within different ecological plant niches.

Methods: We sampled the rhizosphere soil, root, stem, and leaf endosphere of field-grown poplar trees (Populus tremula × Populus alba) and applied 16S rRNA amplicon pyrosequencing to unravel the bacterial communities associated with the different plant habitats.

Results: We found that the structural variability of rhizosphere microbiomes in field-grown poplar trees (P. tremula × P. alba) is much lower than that of the endosphere microbiomes. Furthermore, our data not only confirm microbiome niche differentiation reports at the rhizosphere soil-root interface but also clearly show additional fine-tuning and adaptation of the endosphere microbiome in the stem and leaf compartment. Each plant compartment represents an unique ecological niche for the bacterial communities. Finally, we identified the core bacterial microbiome associated with the different ecological niches of Populus.

Conclusions: Understanding the complex host-microbe interactions of Populus could provide the basis for the exploitation of the eukaryote-prokaryote associations in phytoremediation applications, sustainable crop production (bio-energy efficiency), and/or the production of secondary metabolites.

Keywords: 16S rRNA amplicon pyrosequencing; Bacterial microbiome; Endosphere; Microbiome niche differentiation; Populus tremula × Populus alba; Rhizosphere.

Fig. 1

Average Good’s coverage estimates (%) and rarefaction curves of individual poplar trees per plant compartment (a rhizosphere soil, b root, c stem, d leaf). Good’s coverage estimates represent averages of 15 independent, clonally replicated poplar trees (rhizosphere soil and root samples) and 11 replicates (stem and leaf samples) (± standard deviation) and were calculated in mothur based on 10,000 iterations. Lowercase letters represent statistical differences at the 95% confidence interval (P < 0.05). Rarefaction curves were assembled showing the number of OTUs, defined at the 97% sequence similarity cut-off in mothur, relative to the number of total sequences. The dashed vertical line indicates the number of sequences subsampled from each sample to calculate alpha diversity estimates (Fig. 2)

Fig. 2

Alpha diversity estimates of the bacterial communities. a OTU richness estimates (number of observed OTUs). b Pielou’s evenness estimates. c Inverse Simpson diversity indices. Box plots display the first (25%) and third (75%) quartiles, the median and the maximum and minimum observed values within each data set. Alpha diversity estimates represent 15 biological replicates for the rhizosphere soil and root samples and 11 replicates for the stem and leaf samples and were calculated in mothur with 10,000 iterations. Data were analyzed by means of one-way ANOVAs and Tukey-Kramer post hoc comparisons. The overall plant compartment effects (F(DFn, DFd) and P value) are displayed at the top of each graph. Significant differences (P < 0.05) across plant compartments are indicated with lowercase letters

Fig. 3

Plant compartment drives the composition of the bacterial communities at the OTU level. a Principle component analysis (PCA) of square-root transformed samples based on rarefaction to 2000 reads per sample. OTUs were defined at a 97% sequence similarity cut-off in mothur. OTUs differentiating the plant compartments are displayed as vectors on the PCA plots. b Hierarchical clustering (group average linkage) of the samples based on Bray–Curtis dissimilarity. Similarities based on Bray–Curtis (b) were superimposed on the PCA plot. PCA and hierarchical clusters were based on 15 biological replicates (rhizosphere soil and root samples) and 11 biological replicates (stem and leaf samples) and were constructed in PRIMER 7 with 10,000 iterations

Fig. 4

Phylum distribution of the OTUs. Relative sequence abundance of bacterial phyla associated with the rhizosphere soil and the root, stem and leaf endosphere. Proteobacteria OTU has been replaced by 5 OTUs at the subclass level (alpha, beta, delta, epsilon, gamma). Biological replicates (15 replicates for the rhizosphere soil and root samples and 11 replicates for the stem and leaf samples) are displayed in separate stacked bars. Major contributing phyla are displayed in different colours and minor contributing phyla are grouped and displayed in grey. Total relative abundances of all phyla and significant effects across plant compartments are listed in Additional file 4

Fig. 5

Top OTU members of the bacterial microbiome associated with the plant niches. Taxonomic dendrogram showing the core bacterial microbiome of each plant compartment. Color ranges identify phyla within the tree. Colored bars represent the relative abundance of each OTU in the plant compartments. Taxonomic dendrogram was generated with one representative sequence of each OTU using Unipro UGENE and displayed with the use of iTOL (Interactive Tree Of Life). Total relative abundances of all OTUs and significant effects across plant compartments are listed in Additional file 5