Plant domestication shapes rhizosphere microbiome assembly and metabolic functions

Abstract

Background: The rhizosphere microbiome, which is shaped by host genotypes, root exudates, and plant domestication, is crucial for sustaining agricultural plant growth. Despite its importance, how plant domestication builds up specific rhizosphere microbiomes and metabolic functions, as well as the importance of these affected rhizobiomes and relevant root exudates in maintaining plant growth, is not well understood. Here, we firstly investigated the rhizosphere bacterial and fungal communities of domestication and wild accessions of tetraploid wheat using amplicon sequencing (16S and ITS) after 9 years of domestication process at the main production sites in China. We then explored the ecological roles of root exudation in shaping rhizosphere microbiome functions by integrating metagenomics and metabolic genomics approaches. Furthermore, we established evident linkages between root morphology traits and keystone taxa based on microbial culture and plant inoculation experiments.

Results: Our results suggested that plant rhizosphere microbiomes were co-shaped by both host genotypes and domestication status. The wheat genomes contributed more variation in the microbial diversity and composition of rhizosphere bacterial communities than fungal communities, whereas plant domestication status exerted much stronger influences on the fungal communities. In terms of microbial interkingdom association networks, domestication destabilized microbial network and depleted the abundance of keystone fungal taxa. Moreover, we found that domestication shifted the rhizosphere microbiome from slow growing and fungi dominated to fast growing and bacteria dominated, thereby resulting in a shift from fungi-dominated membership with enrichment of carbon fixation genes to bacteria-dominated membership with enrichment of carbon degradation genes. Metagenomics analyses further indicated that wild cultivars of wheat possess higher microbial function diversity than domesticated cultivars. Notably, we found that wild cultivar is able to harness rhizosphere microorganism carrying N transformation (i.e., nitrification, denitrification) and P mineralization pathway, whereas rhizobiomes carrying inorganic N fixation, organic N ammonification, and inorganic P solubilization genes are recruited by the releasing of root exudates from domesticated wheat. More importantly, our metabolite-wide association study indicated that the contrasting functional roles of root exudates and the harnessed keystone microbial taxa with different nutrient acquisition strategies jointly determined the aboveground plant phenotypes. Furthermore, we observed that although domesticated and wild wheats recruited distinct microbial taxa and relevant functions, domestication-induced recruitment of keystone taxa led to a consistent growth regulation of root regardless of wheat domestication status.

Conclusions: Our results indicate that plant domestication profoundly influences rhizosphere microbiome assembly and metabolic functions and provide evidence that host plants are able to harness a differentiated ecological role of root-associated keystone microbiomes through the release of root exudates to sustain belowground multi-nutrient cycles and plant growth. These findings provide valuable insights into the mechanisms underlying plant-microbiome interactions and how to harness the rhizosphere microbiome for crop improvement in sustainable agriculture. Video Abstract.

Keywords: Microbial interaction network; Microbial metabolic functions; Plant domestication; Rhizosphere microbiomes; Root exudation; Wheat.

Fig. 1

The worldwide distribution and plant phenotypes of domesticated and wild tetraploid wheats. A, B Phylogenetic tree of wheat samples and geographic distribution. The phylogenetic tree of tetraploid wheat genotypes was constructed based on their whole-genome sequences that were obtained from International Wheat Genome Sequencing Consortium (IWGSC). MEGA-X program was applied to generate neighbor-joining tree with 1000 bootstraps. C Three domesticated accessions (T. turgidum ssp. dicoccon) including D1 from different wheat-growing regions of España, D2 (Mexicanos), and D3 (Kazakhstan) and three wild emmer accessions (T. turgidum ssp. dicoccoides) including W1 (Turkey), W2 (Syria), and W3 (Jordan) were calculated plant phenotypes like plant height, thousand grain weight, and ratios of seed length and width at the heating stage of these wheats. Error bars represent standard errors (n = 4). Different lowercase letters above the bars indicate significant differences (P < 0.05), based on Kruskal–Wallis test

Fig. 2

Rhizosphere amplicon sequence variants (ASVs) responsible for the community differences in the wild wheats and domesticated wheats that are calculated by a differential abundance test and random forest classification. A and B The volcano plot illustrating the enrichment and depletion patterns of rhizosphere bacterial and fungal microbiomes in the three wild wheats compared with three domesticated wheat accessions. The ASVs were colored by their categorization as “wild enriched,” “domesticated enriched,” and “non-differential” according to their values of Log2 (count per million) and Log2 (fold change). DI, depleted index; DSI, dissimilarity index. C and D Joyplots showing the relative abundance profiles of top 20 ASVs in bacterial and fungal communities that are revealed by a random forest (RF) classifier. The tenfold validation was performed to evaluate the accuracy of RF model and to select minimum number of ASVs with the lowest prediction error rate. The top ASVs on the genus level are listed along the y-axis representing their importance in contributing to the accuracy of domesticated and wild wheats prediction by calculating their mean decrease accuracy in the RF model

Fig. 3

Rhizosphere microbial interkingdom association networks and node-level topological features. A and B Interkingdom co-occurrence networks in the domesticated and wild wheats. Only compositionality-robust (|p|> 0.7) and statistically significant (q<0.01) correlations were shown. The size of each node indicates the relative abundance of each ASV. The color of each node represents the bacteria or fungi taxa. Blue solid lines represent co-presence associations, and red line represents mutual exclusive correlations. The thickness of each link line is proportional to the correlation coefficients of the connections. The keystone taxa and dominant modules for each networks were also shown. C and D Box graphs illustrating the node-level topological features of each networks, including betweenness and degree. Comparison of these two features demonstrating the high degree and low betweenness for the keystone taxa. Bar diagrams showing the proportion of inter- and intra-kingdom edges of positive or negative correlations in the rhizosphere network. The significance of differences between domesticated and wild wheats was determined by Kruskal–Wallis test

Fig. 4

Functional profiles of rhizosphere microbiomes in the domesticated and wild wheats. A KO functional categories and pathways that were significantly enriched in domesticated wheats are marked in blue; those significantly enriched in wild wheats are marked in orange. All functional categories were determined using the two-tailed Wilcoxon test. B Distribution of enriched functional genes associated with different pathways. KO functional categories that were significantly enriched in domesticated or wild wheats were separately analyzed. Only the dominant KO functional categories (relative abundance > 0.07%) are shown in the histogram and are linked. The data were visualized using Circos (Version 0.69, http://circos.ca/)

Fig. 5

A–D Metabolite-wide association study (MWAS) for enriched rhizosphere bacteria and fungi in domesticated and wild wheats. Heatmap illustrating the statistically significant and positive associations among rhizosphere-enriched ASVs, aboveground plant phenotypes, and enriched metabolites, with associated phylogenetic tree of obtained ASVs from SILVA SSU 138. Only ASVs that were correlated with both phenotypes and root exudates with correlation coefficient |ρ|> 0.5. Each tip indicates a single ASV labelled according to the genus name. The color of branch in the phylogenetic tree represents phyla. Histogram on the top shows the number of positive (marked red) or negative (marked blue) associations registered for each variable. PH, plant height; CC, chlorophyll content; EL, ear length; SSL, subsegment length; tiller; TGW, thousand grain weight; SL, seed length, SW, seed width

Fig. 6

Response of root morphology traits after rhizosphere microbiota inoculation. A Microbial inoculation experiment for domesticated and wild wheat. Group 1, all selected wheat accessions without any addition of inoculum suspension. Group 2, all accessions were inoculated with corresponding inoculum suspension that was generated by mixing rhizospheric soil into TSB medium. Five replicates were set for all treatments. B Root length and root average diameter in the domesticated and wild wheat under the control and inoculation treatments. Error bars represent standard errors (n = 5). The significance of differences between group 1 and group 2 was determined by Kruskal–Wallis test. C Inoculation experiment of group 3 that only contains bacterial isolates (Microbacterium mitrae). D Root architecture traits under control and inoculation treatments were scanned and measured using Microtek ScanMaker i800 plus system. E Seedling fresh/dry weight and root morphology traits were measured. Error bars represent standard errors (n = 5). Different letters indicate significantly different groups (P < 0.05, Kruskal–Wallis test)

Fig. 7

Conceptual model illustrating the plant domestication shapes rhizosphere microbiome assembly and metabolic functions