Synthetic community derived from grafted watermelon rhizosphere provides protection for ungrafted watermelon against Fusarium oxysporum via microbial synergistic effects

Abstract

Background: Plant microbiota contributes to plant growth and health, including enhancing plant resistance to various diseases. Despite remarkable progress in understanding diseases resistance in plants, the precise role of rhizosphere microbiota in enhancing watermelon resistance against soil-borne diseases remains unclear. Here, we constructed a synthetic community (SynCom) of 16 core bacterial strains obtained from the rhizosphere of grafted watermelon plants. We further simplified SynCom and investigated the role of bacteria with synergistic interactions in promoting plant growth through a simple synthetic community.

Results: Our results demonstrated that the SynCom significantly enhanced the growth and disease resistance of ungrafted watermelon grown in non-sterile soil. Furthermore, analysis of the amplicon and metagenome data revealed the pivotal role of Pseudomonas in enhancing plant health, as evidenced by a significant increase in the relative abundance and biofilm-forming pathways of Pseudomonas post-SynCom inoculation. Based on in vitro co-culture experiments and bacterial metabolomic analysis, we selected Pseudomonas along with seven other members of the SynCom that exhibited synergistic effects with Pseudomonas. It enabled us to further refine the initially constructed SynCom into a simplified SynCom comprising the eight selected bacterial species. Notably, the plant-promoting effects of simplified SynCom were similar to those of the initial SynCom. Furthermore, the simplified SynCom protected plants through synergistic effects of bacteria.

Conclusions: Our findings suggest that the SynCom proliferate in the rhizosphere and mitigate soil-borne diseases through microbial synergistic interactions, highlighting the potential of synergistic effects between microorganisms in enhancing plant health. This study provides a novel insight into using the functional SynCom as a promising solution for sustainable agriculture. Video Abstract.

Keywords: Community simplification; Disease suppression; Interspecific synergy; Synthetic community.

Fig. 1

The consortium promoted plant growth and alleviated disease. a–d Shoot height, fresh weight, dry weight, and root weight of the ungrafted watermelon plants. e–h Representative images of ungrafted watermelon plants at 6 weeks post-inoculation with sterile water (CK), SynCom (SBC), SynCom and F. oxysporum (SBC + FON), and F. oxysporum (FON). i Fusarium wilt disease index under different treatments (CK, SBC, SBC + FON, and FON). j F. oxysporum density in the rhizosphere of different treated plants. k Relative control effect of the inoculated SynCom. Relative control effect (%) = [(control disease index—treatment disease index) / control disease index] × 100. Here, control refers to FON group, treatment refers to SBC + FON group. Different letters above the boxes indicate significant differences at P < 0.05 according to the Duncan test (n = 8–10). CK ungrafted watermelon plants inoculated with sterile water, SBC ungrafted watermelon plants inoculated with SynCom, SBC + FON ungrafted watermelon plants inoculated with SynCom and F. oxysporum, FON ungrafted watermelon plants inoculated with F. oxysporum

Fig. 2

Changes in the rhizosphere microbial community composition and function profile in plants inoculated with SynCom. a The bacterial α diversity of CK, SBC, SBC + FON, and FON groups (n = 8 biologically independent plants). b Bray–Curtis similarity analysis of bacterial communities. c Bacterial relative abundance in each treated group at the genus level (top 10). d Relative abundances of the core microbes ASVs in the rhizosphere of different treated group. Matched V4–V5 subregion of the strain 16 S rRNA gene to ASVs as an indicator of strain presence and relative abundance in the rhizosphere (Table S4). e Correlation analysis of the sum of relative abundances of ASVs corresponding to each of the 16 strains with the density of Fusarium oxysporum in each treated group. f Reporter score bar plot comparing the abundance of KEGG pathways in different treated group (n = 3). Dashed lines represent a reporter score of 1.69, which is the threshold for indicating significant differences in such analyses. The red bars show the metabolic pathways that were significantly enriched in the SBC or SBC + FON groups. The blue bars show the metabolic pathways that were significantly enriched in the CK or FON groups. g Differences in the abundance (TPM) of the functional genes that are involved in biofilm formation—Pseudomonas aeruginosa pathway. The gene abundance shown here is Z-score standardized. h Genes significantly enriched in the biofilm formation—Pseudomonas aeruginosa pathway in the SBC group traced back to species taxonomy using meta-linking methods. i Genes significantly enriched in the biofilm formation—Pseudomonas aeruginosa pathway in the SBC + FON group traced back to species taxonomy

Fig. 3

In vitro interaction matrix and substrate depletion profiles between individual SynCom strains. a The mean OD₆₀₀ of the cultures of different strains in fresh medium and the respective spent medium (SM) was determined from three independent experiments. OD₆₀₀ spent/fresh values of > 1 and < 1 indicated promotion and inhibition of the strain growth, respectively. b Using the OD₆₀₀ spent/fresh values, a pairwise interaction matrix was generated. Interactions where the ratio was significantly > 1 (P < 0.05) are indicated with ( +), interactions where it was significantly < 1 are indicated with ( −), and interactions where the ratio did not significantly vary from 1 are indicated with (0). c Depletion profiles of substrates after bacterial growth to stationary phase in the fresh medium were determined by untargeted MS from three independent experiments. Metabolomic features (rows) that significantly decreased (P < 0.05 compared to fresh media) compared to fresh medium for the 16 strains are shown in red. Dark red indicates strong depletion, while white indicates no depletion of the metabolomics feature. d Pairwise overlap in depleted metabolomic features relative to the total number of depleted metabolomic features (shown in Fig. S15) of every individual strain, e.g., P. mexicana Q1 shares 208 metabolomic features from its set of 454 depleted metabolomic features with P. aquiterrae Q2, corresponding to 45.81%. As P. aquiterrae Q2 in contrast only depletes 284 metabolomic features in total from fresh medium, this corresponds to an overlap of 73.24% of shared metabolites between P. aquiterrae Q2 and P. mexicana Q1 relative to the total set of P. aquiterrae Q2 depleted metabolomics features. e Correlation analysis of OD₆₀₀ spent/fresh and the pairwise overlap in depletion profiles. The blue dots represent growth involving all strains, the red dots only represent the growth of P. aeruginosa Q6 in the SM of the other seven strains. f Potential cross-feeding metabolites were identified by comparing the SM metabolic profiles (determined by untargeted MS) of the two strains. The blue color represents that one of the strains produces the metabolite and the red color represents that its partner can consume the metabolite

Fig. 4

Effects of various simplified SynComs on plant growth. a Representative images of ungrafted watermelon plants at 6 weeks post-inoculation with sterile water (CK), top 4 species ranked in network degree (SSC4D), top 8 species ranked in network degree (SSC8D), 8 species with synergistic effect (SSC8), and all 16 core strains (SBC). b–d Shoot height, root weight, and dry weight of plants. Letters indicate significant differences (P < 0.05)