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Protorhabditis nematodes and pathogen-antagonistic bacteria interactively promote plant health

Microbiome volume 12, Article number: 221 (2024) Cite this article

Abstract

Background

Fertilization practices control bacterial wilt-causing Ralstonia solanacearum by shaping the soil microbiome. This microbiome is the start of food webs, in which nematodes act as major microbiome predators. However, the multitrophic links between nematodes and the performance of R. solanacearum and plant health, and how these links are affected by fertilization practices, remain unknown.

Results

Here, we performed a field experiment under no-, chemical-, and bio-organic-fertilization regimes to investigate the potential role of nematodes in suppressing tomato bacterial wilt. We found that bio-organic fertilizers changed nematode community composition and increased abundances of bacterivorous nematodes (e.g., Protorhabditis spp.). We also observed that pathogen-antagonistic bacteria, such as Bacillus spp., positively correlated with abundances of bacterivorous nematodes. In subsequent laboratory and greenhouse experiments, we demonstrated that bacterivorous nematodes preferentially preyed on non-pathogen-antagonistic bacteria over Bacillus. These changes increased the performance of pathogen-antagonistic bacteria that subsequently suppressed R. solanacearum.

Conclusions

Overall, bacterivorous nematodes can reduce the abundance of plant pathogens, which might provide a novel protection strategy to promote plant health.

Video Abstract

Background

Every year, plant pathogens globally cause around 10–20% crop losses [1, 2]. One of the most well-known plant pathogens is Ralstonia solanacearum, which causes devastating bacterial wilt in a wide range of plants, including tomatoes, potatoes, bananas, and other crops [3]. Bacterial wilt is traditionally controlled by synthetic chemicals, such as bactericides [4]. While these approaches are usually effective in the short term, they are non-sustainable and may negatively impact the environment. Frequent and extensive use of synthetic chemicals may also lead to the development of resistance in plant pathogens [5]. Therefore, environmentally friendly approaches to control plant pathogens are urgently needed to sustain crop yields and to ensure future ecological integrity.

So far, many sustainable practices are in practice, such as optimized crop rotations, and minimized chemical inputs and performance of conservation tillage [6,7,8,9]. Among them, one of the most important ones to control plant pathogens is applying “green fertilizers” containing organic matter and plant probiotics [10, 11]. Organic matter derived from especially plant residues is essential to soil health, as it contributes to maintaining soil structure, water retention, nutrient cycling, and plant health, mainly through supporting the activity of beneficial soil microorganisms [12]. Furthermore, using plant probiotics to combat plant diseases has been proposed as a sustainable approach for pathogen control and for supporting plant performance [13, 14]. For instance, mature compost containing biocontrol agents (e.g., Bacillus subtilis and Pseudomonas stutzeri) might replace chemical fertilizers by providing equivalent levels of nutrients but at the same time improving soil health [15].

Green fertilizers also modify the soil microbiome in favor of indigenous soil microbes, such as Bacillus and Pseudomonas bacteria that enhance plant disease suppression [16, 17]. In addition, other trophic levels in the soil food web are stimulated by bio-organic fertilizer application [18]. Previous research showed that bio-organic fertilizer application increased abundances of protists, especially bacterivorous protists, which subsequently promoted plant growth and controlled Fusarium wilt by regulating the soil microbiome [19, 20]. Myxobacteria increased by bio-fertilizer management were also shown to control cucumber Fusarium wilt by stimulating soil antagonistic bacteria, such as Microvirga and Cupriavidus [21]. However, current soil suppression mechanisms induced by different fertilization practices concentrate on the microbiome, while links among bio-organic fertilizers, soil suppressiveness, and larger soil fauna remain unknown.

Among soil fauna, nematodes are by far most numerous and represent major players of ecosystem functions like nutrient cycling that positively affects plant performance [22]. The main functional groups of nematodes are bacterivores, fungivores, herbivores, omnivores, and predators [23]. Most focus has been on herbivores due to their direct negative role on plant health and as catalyzers of other plant pathogenic microorganisms such as bacteria, fungi, and viruses [24, 25]. However, more and more researchers have found potential benefits of free-living nematodes for plants. Among them, bacterivorous nematodes have been associated with fostering nutrient cycling [26,27,28]. Predation of bacterivores nematodes on bacteria has been shown to increase P cycling to result in enhanced plant growth [29]. Nematodes belonging to the genus Protorhabditis are among the most numerous bacterivores in soils, especially in moist and organic-rich soils [30]. Protorhabditis spp. can stimulate the overall abundance of bacteria, thereby accelerating organic matter mineralization leading to increased plant-available nutrients, such as nitrogen and phosphorus [31]. Furthermore, organic matter amendments can enhance bacterivores by improving microbial prey abundance, as well as the structure and nutrient status of soils [32]. A study analyzing the metabolic footprint of nematodes at a local scale also showed that carbon addition inhibited the abundance of herbivorous nematodes and stimulated the abundance of bacterivorous nematodes [33]. Bacterivores normally have special food preferences, with not all bacterial taxa being equally preyed upon. This selective feeding can alter bacterial community composition [34,35,36]. This nuanced interaction highlights the potential of nematodes as regulators of microbial diversity and structure within soil ecosystems. However, the role of nematodes in mediating soil microbiota to promote plant health remains unknown. Understanding how nematodes influence the intricate web of soil microbiota and its subsequent impact on plant health could unveil novel strategies for sustainable agriculture and ecosystem management.

Here, we aimed to identify nematode taxa and functional groups linked to disease suppression and plant health (Fig. 1). We used Illumina amplicon sequencing and qPCR to investigate the diversity and community composition of nematodes but also bacteria as major disease and biocontrol agents in tomato rhizospheres in fields treated with no-, chemical- and bio-organic fertilization regimes. We performed subsequent in vitro and greenhouse experiments to validate the interactive effects of bacterivorous nematodes with nine genera of bacteria on tomato health, including pathogenic R. solanacearum and pathogen-antagonistic Bacillus spp. We hypothesized that as follows: (1) Bio-organic fertilizer application promotes nematode abundances, specifically bacterivorous nematodes, (2) bacterivorous nematodes change microbiome composition by favoring pathogen-antagonistic bacteria, and (3) bacterivorous nematode-induced microbiome changes will suppress R. solanacearum and tomato bacterial wilt disease.

Fig. 1
figure 1

Flow chart of the experiments. The study comprised several experiments: one field experiment, three greenhouse experiments, and five in vitro experiments. In the field experiment, we investigated whether bio-organic fertilizer application changes nematode communities and enhances their abundance. From there, we isolated different anti-pathogenic bacteria and bacterivorous nematodes. We then tested the importance of the bacterivores (greenhouse expt. 1) and the microbiome (greenhouse expt. 2) in pot experiments and assessed the importance of bacterivores nematodes in co‑colonization with Bacillus for promoting plant health (greenhouse expt. 3). We also examined direct predation of bacterivorous nematodes on pathogenic R. solanacearum (in vitro expt. 1) and selective predation of nematodes on bacteria with different anti-pathogenic abilities (in vitro expts. 2–3). Finally, the co-cultural experiment validated the effects of bacterivores that promoted the expression in anti-pathogenic abilities of Bacillus, leading to a decrease of R. solanacearum (in vitro expts. 4–5)

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Methods

Field experiment design

To investigate the effects of different fertilization on soil nematode and microbial communities, we performed a long-term field experiment. The study site was (starting in March 2013) located at the Nanjing Institute of Vegetable Science in a subtropical monsoon climate region in China (31°43′ N, 118°46′ E). The annual average temperature is 16.7 °C, and precipitation is 959 mm. Soil is silty clay. Three treatments of the field experiment were selected for this study: (1) Control with no fertilizer (Ctrl); (2) chemical fertilizer treatment (CF), where a total of 120 kg ha−1 nitrogen (N), 180 kg ha−1 phosphorus (P), and 120 kg ha−1 potassium (K) were added in the sample collection season; and (3) bio-organic fertilizer treatment (BF), where 7500 kg ha−1 of bio-organic fertilizer was applied, corresponding to a total nutrient input of 138.75 kg ha−1 N, 60 kg ha−1 P, and 109.5 kg ha−1 K. The bio-organic fertilizer was produced by inoculating 5% (v/dw) Bacillus amyloliquefaciens SQR9 [37], which was isolated in our laboratory, into chicken manure compost, and then fermented for 7 days. In addition, the nutrient differences (nitrogen, phosphorus, and potassium) among fertilizers applied to each treatment were tested and compensated using mineral fertilizers (urea, superphosphate, potassium sulfate). Each treatment had 3 independent replicate plots, and each replicate contained 40 tomato plants (Solanum lycopersicum). The tomato variety used in this experiment was a commercial cultivar, “Shi Ji Hong Guan,” one of the early ripening tomato cultivars with round, large, and red fruits. A bioassay for disease incidence was performed at the end of the experiment during the harvest season in October 2019. The assessment was based on observations of typical wilt symptoms, including necrosis and leaf drooping [37]. The disease incidence was calculated by counting the number of tomato plants with bacterial wilt among the total number of tomato plants in each plot. One value was obtained from each plot; thus, each treatment had three disease incidence replicates.

Soil sampling

Soil (bulk and rhizosphere) samples from all treatments were collected during the harvest season in October 2019. In brief, 6–8 healthy tomato plants were randomly extracted in each treatment plot. Loosely adhering soil was gently shaken off before rhizosphere soil was collected, according to Deng et al. [13]. Soils were passed through 2-mm meshes to remove roots, stones, and larger soil animals and then were stored at − 80 °C and 4 °C prior to DNA extraction and physicochemical analyses. Soil nematodes were extracted from 100-g field-moist soil by a modified Baermann method, and total nematode abundance was counted under a microscope (Nikon ECLIPSE Ts2) at 40 × magnification [38]. Soil pH, moisture, total carbon (TC), total nitrogen (TN), total phosphorus (TP), total potassium (TK), nitrate (NO3−-N), ammonium (NH4+-N), available phosphorus (AP), and available potassium (AK) were determined according to the methods described in Dong et al. [39].

DNA extraction, Illumina MiSeq sequencing, and real-time qPCR analysis

Soil DNA was extracted from 10-g soil using the DNeasy® PowerMax® Soil Kit (Qiagen, Germany), according to the manufacturer’s instructions. For MiSeq sequencing, the DNA extracted served as a template for the amplification of the V4 hypervariable regions of the bacteria 16S rRNA genes targeting primer pairs were 515F (5′-GTGCCAGCMGCCGCGGTAA-3′)/806R (5′-GGACTACHVGGGTWTCTAAT-3′), which produces an amplicon of ~ 250 base pairs (bp) [40] and nematode 18S rRNA genes using the paired primers NF1-F (5′-GGTGGTGCATGGCCGTTCTTAGTT-3′)/18Sr2b (5′-TACAAAGGGCAGGGACGTAAT-3′) [41] and the eukaryote-wide V4_1f (5′-CCAGCASCYGCGGTAATWCC-3′)/TAReukREV3 (5′-ACTTTCGTTCTTGATYRA-3′) [42], which both produce an amplicon of ~ 350 base pairs (bp). Detailed information regarding the PCR program and barcode strategy for each sample is provided in the supplementary material. The amplification product was sequenced on an Illumina MiSeq platform at Personal Biotechnology Co., Ltd. (Shanghai, China). The fliC gene was used to quantify the copy number of R. solanacearum with specific primers (forward, 5′-GAACGCCAACGGTGCGAACT-3′; reverse, 5′-GGCGGCCTTCAGGGAGGTC-3′) [43]. The abundance of Bacillus was quantified by qPCR with specific primer (forward, 5′-ATGTTAGCGGCGGACGGGTGAG-3′; reverse, 5′-AAGTTCCCCAGTTTCCAATGACC-3′) [44]. qPCR analyses were performed with a qTOWER 2.2 system of Analytik Jena (Jena, Germany) using SYBR green I fluorescent dye detection in 20-μL volumes, which contained 2 μL of template, 10 μL of SYBR Premix Ex Taq (TaKaRa Bio Inc., Japan), and 0.4 μL of both forward and reverse primers (10 μM each) in 96-well plates. All qPCRs were performed using the standard temperature profile [45]. In brief, the qPCR conditions were as follows: 30 s at 95 °C, 40 cycles consisting of 5 s at 95 °C, 34 s at 60 °C, and 60 s at 72 °C, 1 s at 95 °C. Each sample was analyzed in three replicates, and the results were expressed as log10 values (target copy number per gram soil in each treatment).

Bioinformatic analysis

Bacterial and nematode raw sequences were split according to their unique barcodes. Furthermore, adaptors and primer sequences were trimmed using cutadapt (https://github.com/marcelm/cutadapt). Subsequently, the trimmed bacterial and nematode sequences were processed with the UPARSE pipeline according to previously established protocols [46]. Bacterial sequences with expected errors > 1.0 or a length shorter than 200 bp and nematode sequences with expected errors > 1.0 or a length shorter than 350 bp were removed. After discarding singletons, the remaining bacterial and nematode sequences were respectively categorized into zOTUs and zOTUs at 100% similarity [47, 48]. The RDP database (http://rdp.cme.msu.edu/) was used to assign the taxonomic identity of each phylotype of bacteria [49], and the PR2 database was used to assign the taxonomic identity of phylotypes for nematode [50]. We further assigned taxonomic nematode zOTUs into different trophic groups (bacterivores, fungivores, plant parasites, and omnivores/predators) according to their feeding mode [41].

Culturable nematodes, bacterial strains, and their growth conditions

Bacterivorous nematodes, Protorhabditis, were isolated from filed soil in December 2019 by the Ecological Laboratory of Nanjing Agricultural University and cultivated in nematode growth medium (NGM) agar plates [51] at 20 °C for 1 week by feeding on E. coli OP50. Prior to utilization, nematodes were washed with disinfectant (containing 0.1% streptomycin sulfate and 0.002% cycloheximide) and sterilized water to minimize the effects of Escherichia coli on the nematode characteristic, including predation and movement [52].

Through high-throughput isolation and identification, bacterial isolates from tomato rhizosphere soil were performed according to previously described protocols [13, 53]. In brief, tomato roots were washed in PBS on a shaking platform for 30 min at 170 rpm. For limiting dilution, homogenized rhizosphere soils were sedimented for 15 min, and the supernatant was empirically diluted, distributed, and cultivated in 96-well microliter plates with 200-mL tryptic soy broth (TSB) medium in each well. Then, a two-step barcoded PCR protocol in combination with Illumina HiSeq was adopted to define the sequences of bacterial 16S rRNA genes of rhizosphere bacteria. Afterward, sequences were clustered into zOTUs with greater than 99% 16S rRNA gene similarity and submitted to the RDP database for taxonomic identification. Finally, 42 isolate genera were obtained in this step, and according to high-throughput sequencing analysis results, the activated R. solanacearum and a variety of taxonomic bacteria strains (Arthrobacter, Bacillus, Fictibacillus, Paenibacillus, Pedobacter, Phycicoccus, Lysinibacillus, Mesorhizobium, and Microvirga) were selected for subsequent experiments. The ability of all bacterial isolates to inhibit the growth of R. solanacearum was tested according to previous research [54].

In vitro experiment systems and setup

In vitro experiment 1

Predation behavior of bacterivorous nematodes on R. solanacearum was observed. A total of 5 μL of R. solanacearum solution (concentration: 106 cfu mL−1), and about 100 Protorhabditis individuals, were placed on two sides of nematode growth medium. Within 24 h, nematodes’ moving and feeding behavior towards R. solanacearum was observed and recorded under a 40 × inverted microscope (Nikon ECLIPSE Ts2).

Growth of bacterivorous nematode abundance through preying on R. solanacearum was also evaluated. Furthermore, 10 μL of R. solanacearum (concentration: 106 cfu mL−1) solution was spread evenly on nematode growth medium, and the nematode growth medium without R. solanacearum coating was set as control. All mediums were placed in a 30 °C incubator for 5 h to ensure the R. solanacearum growth, and then 100 Protorhabditis individuals were inoculated at the center of the medium at 20 °C. After 6-, 12-, 18-, and 24-h cultures, the nematode abundances were counted, respectively. All treatments were performed with six biological replicates.

In vitro experiment 2

To investigate the selective predation of bacterivorous nematodes to bacteria, we performed an in vitro predation test experiments. A total of 5 μL of each targeted strain (concentration: 106 cfu mL−1) and 5 μL of R. solanacearum with the same concentration were placed on opposite sides of the nematode growth medium. One-hundred individual nematodes were placed on the center of nematode growth medium, and then nematode growth medium was placed in a 20 °C incubator for 6 h to count the nematode abundances consuming bacteria on both sides of the plate. The nematode predation preference index was calculated as (A − B)/(A + B) × 100%, where A and B denote nematode abundances on the test solution side and R. solanacearum solution side, respectively. All treatments were performed with six biological replicates.

In vitroexperiment 3

Based on the result of the second in vitro experiment, the mutant Bacillus strain (Mut_B, disrupted in the bacillomycin D pathway) and wild-type Bacillus strain (WT_B), which were stored in Jiangsu Provincial Key Lab of solid Organic Waste Utilization of Nanjing Agricultural University, were used to confirm the effect of the anti-pathogen ability of bacteria on bacterivorous nematode predation. A total of 5 μL of mutant Bacillus strain and wild-type Bacillus strain (concentration: 106 cfu mL−1) were placed on opposite sides of nematode growth medium. One-hundred individual nematodes were inoculated at the center of the medium at 20 °C. After 6-h culture, the nematode abundance that preys on bacteria was counted on both sides of nematode growth medium. All treatments were performed with six biological replicates.

In vitro experiment 4

To investigate the effect of bacterivorous nematodes on the ability of bacteria to antagonize R. solanacearum, we performed an in vitro co-culture experiment. A total of nine targeted strains (Arthrobacter, Bacillus, Fictibacillus, Paenibacillus, Pedobacter, Phycicoccus, Lysinibacillus, Mesorhizobium, and Microvirga) was selected to test. Among these strains, Bacillus, Fictibacillus, and Lysinibacillus were stimulated by bacterivorous nematodes in fields, which also has been reported as biocontrol bacteria in agricultural production [54,55,56]. Other six bacterial strains were selected randomly in soils to test as nonantagonistic bacteria. These bacterial solution with the final concentration of 106 cfu mL−1 and Protorhabditis with a concentration of 1500 ind. mL−1 were supplied in 10% nutrient agar (NA) liquid medium in a 96-well plate system (final volume of 200 μL per well), which were cultured for 24 h with six replicates per treatment at 20 °C. There were 19 treatments, including the above 9 isolation bacterial strains and their pairs with Protorhabditis (Table S1). After 72-h culture, the liquid medium was centrifuged at 4000 rpm for 10 min to get the supernatant of each treatment. In order to obtain the sterilized supernatant, the supernatant of each treatment was filtered by a 0.22-μm sterile filtration membrane. Then, 2 μL of R. solanacearum with a concentration of 106 cfu mL−1 and 20-μL sterilized supernatant were added to each well, and 10% NA medium was supplemented to the whole volume of 200 μL. After 24 h, the suspension turbidity (OD600) was measured as the pathogen-antagonistic ability of each treatment by using SpectraMax M5 (Sunnyvale, CA, USA) at room temperature. All treatments were performed with six biological replicates.

In vitro experiment 5

To investigate the alteration of bacterivorous nematodes on the assembly of a R. solanacearum-suppressing bacterial community against R. solanacearum, we performed an in vitro co-culture experiment. Twenty microliters of nutrient agar (NA) medium with R. solanacearum (concentration: 106 cfu mL−1), each targeted strain (concentration: 106 cfu mL−1), and nematode Protorhabditis (1500 ind. ml−1), was added to 140-μL fresh nutrient broth medium in 96-well plates. There were 20 treatments, including the above 9 isolation bacterial strains in the fourth in vitro experiment and their pairs with Protorhabditis and R. solanacearum (Table S2). The suspensions were sprayed on the R. solanacearum growth selective medium, and the amount of R. solanacearum was quantified after 24-h culture. All treatments were performed with six biological replicates.

Greenhouse experiment systems and setup

Soils collected from the experiment field in chemical treatment were passed through 2-mm meshes to remove the impurities (e.g., roots and stones) and then divided into two parts. One part was sterilized by 75-kGy gamma rays at Nanjing Xiyue Technology Co., Ltd., Nanjing, China. The other part was used to prepare soil suspensions at a volume ratio of 1:10 between soil and sterilized water and passed through a 20 -μm mesh sieve to remove nematodes [57]. The absence of nematodes and eggs in the suspensions was ensured by microscopic observation. The nematode-free suspensions were amended into sterile soil at a volume ratio of 1:2 to produce nematode-free soils. These soils were stored in sealed plastic culture bottles at 25 °C for more than 1 month [58], and the soil moisture was adjusted to 60% of its maximum holding capacity by adding distilled water. In this study, nematode-free soils were obtained as background soils for all greenhouse experiments.

Greenhouse experiment 1

The effect of bacterivorous nematodes Protorhabditis on tomato bacterial wilt was investigated. Nematodes with different abundance levels (0, 200, 400, and 800 Protorhabditis individuals) were inoculated into 200 g of nematode-free soil per pot resulting in the following four treatments: (1) Ctrl, soil without nematodes; (2) Pro1, soil inoculated with 200 Protorhabditis individuals; (3) Pro2, soil inoculated with 400 Protorhabditis individuals; and (4) Pro3, soil inoculated with 800 Protorhabditis individuals. After 20 days of tomato plants transplanting and growth, Protorhabditis nematodes were inoculated, followed by R. solanacearum (105 cfu/g soil) 5 days later. Each treatment contained three components (six plants in each component). The disease incidence in this greenhouse experiment was calculated by counting the number of tomato plants appearing with bacterial wilt among the total number of tomato plants in each component. One value was obtained from each component; thus, each treatment had three incidence replicates.

Greenhouse experiment 2

The effect of bacterivorous nematodes on tomato disease incidence by directly consuming R. solanacearum was investigated. Bacterivorous nematodes (0, 800 Protorhabditis individuals) were inoculated into 200-g sterilized soil resulting in the following two treatments: (1) S_Ctrl, sterile soil without nematodes, and (2) S_P, sterile soil inoculated with 800 Protorhabditis individuals. After 20 days of tomato plants transplanting and growth, Protorhabditis nematodes were inoculated, followed by R. solanacearum (105 cfu/g soil) added to all treatments 5 days later. The disease incidence was calculated as in the 1st greenhouse experiment.

Greenhouse experiment 3

The combinative effect of bacterivorous nematodes and pathogen-antagonistic bacteria on tomato bacterial wilt was investigated. According to our high-throughput sequencing analysis and in vitro experiments results, three bacterial isolates (Bacillus, Lysinibacillus, Fictibacillus) and bacterivores nematode (Protorhabditis) were selected to build combinations in soils. Eight-hundred Protorhabditis individuals and each bacteria solution (107 cfu/g soil) were introduced into 200 g of soil per pot following eight treatments: (1) Ctrl, soil without any nematode and bacteria inoculation; (2) Pro, soil inoculated with 800 Protorhabditis individuals; (3) Bac, soil inoculated with 5-mL Bacillus solution; (4) Pro + Bac treatment, soil inoculated with 800 Protorhabditis individuals and 5-mL Bacillus solution; (5) Lys, soil inoculated with 5-mL Lysinibacillus solution; (6) Pro + Lys, soil inoculated with 800 Protorhabditis individuals and 5-mL Lysinibacillus solution; (7) Fic, soil inoculated with 5-mL Fictibacillus solution; and (8) Pro + Fic, soil inoculated with 800 Protorhabditis individuals and 5-mL Fictibacillus solution. After 20 days of tomato plant transplanting and growth, Protorhabditis nematodes were inoculated, followed by bacterial isolate solution (107 cfu/g soil) 5 days later. Another 5 days later, R. solanacearum (105 cfu/g soil) was inoculated to all treatment soil. The disease incidence was calculated as in the 1st greenhouse experiment.

Statistical analysis

The α-diversity of bacterial and nematode communities in the field experiment was estimated using the nonparametric Shannon index. Bray–Curtis distance and Euclidean distance were calculated by “vegdist” function of vegan package on R 4.1.1 [59]. Differences in community structure between fertilization treatments were tested using permutational multivariate analysis of variance (PERMANOVA), which was performed using the vegan package (function: adonis) with 9999 permutations [59]. Unweighted UniFrac distance metrics were calculated based on phylogenetic trees for community comparisons by the UniFrac function in the GuniFrac package in R 4.1.1 and then visualized using principal coordinate analysis (PcoA) plots (PCoA function in ape) [60]. Comparisons among multiple treatments were performed using one-way analysis of variance (ANOVA) followed by Tukey’s multiple range test, while differences between two groups were analyzed using the t-test. All statistical analyses were conducted using IBM SPSS 23.0 software (SPSS Inc., USA). To investigate the correlation between soil physical–chemical properties and soil nematode composition with disease incidence, Mantel and partial Mantel test was performed with “mantel” and “mantel. Partial” function of vegan package on R 4.1.1 based on Euclidean distance of soil physical–chemical properties and Bray–Curtis distance of nematode composition. Hmisc package in R (version 4.1.1) was used to construct the correlation heatmap between bacterivorous nematodes zOTUs and bacterial zOTUs (average relative abundance > 0.01%) based on the Spearman correlation matrix [61]. As the bacterivorous nematode zOTUs were significantly enriched in low-disease treatment (BF) compared to other treatments (Ctrl and CF), we focused on nematode taxa zOTUs and bacterial taxa zOTUs and used Spearman’s correlation coefficient to evaluate the correlation between significantly different bacterivorous nematodes zOTUs and bacterial zOTUs (average relative abundance > 0.01%). In addition, we calculated the relationship between these bacterial taxa zOTUs and disease incidence from the field experiment based on Spearman correlation. Structural equation model (SEM) analysis was conducted to test the direct and indirect effects of bacterivores, herbivores, bacterial community structure, and key bacterial zOTU 181 at multiple trophic levels on plant disease incidence. The bacterial community structure for the SEM analysis was represented by the first axis of principal coordinate analysis (PCoA) based on the Bray–Curtis distance. We used χ2 test, P-value, degree of freedom(df), the root-mean-square error of approximation (RMSEA), and comparative fit index (CFI) to check the model fitness. The SEM analyses were conducted using Amos 16.0 software (Amos IBM, USA).

The variances of plant disease incidence and abundance of R. solanacearum among different treatments in greenhouse experiments were calculated using one-way analysis of variance (ANOVA) followed by Tukey’s multiple range test. The relationship between disease incidence and abundance of R. solanacearum and Protorhabditis density in soil was calculated based on Spearman correlation.

The box plots illustrating the predation preference of Protorhabditis on bacteria and inhibition of bacteria to R. solanacearum in in vitro experiments were generated using the ggbeeswarm package [62]. The relationships between bacterivores abundance and disease incidence/R. solanacearum density in greenhouse experiments were calculated based on Spearman correlation. In the experiment assessing the increase in nematode Protorhabditis abundance due to predation on R. solanacearum, both ANOVA and independent sample t-tests were used for statistical analysis. ANOVA was applied to examine the changes in Protorhabditis number on plates over different time points, in the presence or absence of R. solanacearum. Independent sample t-tests were used to compare nematode abundance between R. solanacearum — present and R. solanacearum — absent plates at the same time points. Similarly, for assessing the inhibitory effects of different bacterial strains on R. solanacearum with or without nematode presence, both ANOVA and independent sample t-tests were used. ANOVA was employed to compare the inhibitory effects of different bacterial strains on pathogens. Independent sample t-tests were used to compare the inhibitory effects of the same bacterial strain on pathogens with or without nematode presence. In all experiments, the relative change was calculated by subtracting the control group data from the treatment group data, dividing the result by the control group data, and multiplying by 100%. Statistical methods used and main outcomes of the field, greenhouse, and in vitro experiments were listed as Table 1.

Table 1 Statistical methods used and main outcomes of the field, greenhouse, and in vitro experiments
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Results

Field disease incidences and nematode abundance under different fertilization regimes (field experiment)

Disease incidence in bio-organic fertilizer treatment (BF) was 51.3% and 27.5% lower than those in non-fertilizer (Ctrl) and chemical fertilizer (CF) treatments, respectively (Fig. 2a and Table 1). Additionally, the nematode abundance in BF was 127.0% and 54.1% higher than in Ctrl and CF (Fig. 2b and Table 1). Furthermore, the abundances of R. solanacearum in Ctrl and CF were 32.2% and 23.1% higher than those in BF, respectively (Fig. 2c and Table 1). A strong negative correlation existed between nematode abundance and tomato disease incidence in fields based on the Spearman’s rank correlation analysis (R = − 0.87; p = 0.0045; Fig. 1d).

Fig. 2
figure 2

Overall plant, disease, and biological patterns observed in the tomato fields under no fertilizer (Ctrl), applied with chemical (CF), or bio-organic fertilizer (BF). a Disease incidence analysis in experimental fields planted with tomato. b Nematode abundances in numbers g.−1 under different fertilization regimes. c Abundance of R. solanacearum in rhizosphere soil. d Correlation between soil nematode abundance and tomato disease incidence, and gray shading denotes 95% confidence intervals. In a, b, and c, data are plotted as means ± SEs (n = 3), and bars with different letters indicate significant differences as defined by one-way ANOVA with Tukey’s post hoc test (p < 0.05)

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Bio-organic fertilizer promotes abundances of bacterivorous nematodes by increasing soil carbon matter (field experiment)

Bio-organic fertilizer in fields changed the amount of soil nutrients such as soil organic carbon, total nitrogen, available phosphorus, and available potassium (Table S3). Mantel test showed that soil organic carbon was the most important soil property influencing the nematode community structure, including bacterivorous nematodes and herbivore nematodes (Fig. S1a). In addition, soil nitrate nitrogen content affected the nematode community structure. Furthermore, Spearman correlation analysis showed a positive correlation between the relative abundance of bacterivorous nematodes and soil organic carbon (R = 0.800, p < 0.001; Fig. S1b), and there was a marginally significant negative relationship between soil organic carbon and herbivore nematodes (R = − 0.67, p = 0.059, Fig. S1c).

Underlying drivers of nematode and bacterial functional taxa linked to disease incidence (field experiment)

Alpha diversity of nematode communities was not affected by fertilization management (Fig. 3a, Table 1). However, fertilization management shaped the nematode community composition with three distinct clusters for non-fertilized, chemical, and bio-organic treatments, respectively (PERMANOVA test, R2 = 0.511, p < 0.001; Fig. 3b and Fig. S2). Indicator species analysis revealed that five bacterivorous nematodes zOTUs were enriched in BF treatment, including zOTU 74 (Cephalobus), zOTU 112 (Cephalobus), zOTU 241 (Protorhabditis), zOTU 252 (Protorhabditis), and zOTU 731 (Acrobeloides). In contrast, three herbivore nematodes zOTUs (i.e., zOTU 18 (Meloidogyne), zOTU 529 (Rotylenchulus), zOTU 19 (Meloidogyne)) enriched in non-fertilized treatment (Fig. 3c). Among the five bacterivorous nematodes zOTUs, zOTU 112 (Cephalobus), zOTU 252 (Protorhabditis), and zOTU 731 (Acrobeloides) had negative relationships with disease incidence in the field experiment based on Spearman’s correlation analysis (R = − 0.84, p = 0.005; R = − 0.68, p = 0.046; R = − 0.792, p = 0.011; Fig. 3d).

Fig. 3
figure 3

Comparison of nematode community composition and correlations with bacteria and disease incidence under different fertilization treatments. a, b Nematode diversity and community structure in the field experiment shown using principal component analysis (PCA) based on Bray–Curtis distance. Different colors represent different fertilization treatments. c Heatmap showing the relative abundance of nematode zOTUs across various fertilization treatments. The color key indicates z-scores; plus and minus signs indicate positive and negative correlations with disease incidence. Significant differences are marked with different letters (ANOVA with Tukey’s test, p < 0.05). d Heatmap depicting the relationship between the relative abundance of bacterivorous nematode zOTUs, bacterial zOTUs, and disease incidence. Only significant Spearman correlations (p < 0.05) are shown. e Structural equation model (SEM) illustrating how nematode and bacterial communities impact tomato disease incidence. Arrow width reflects the strength of the relationships: red arrows indicate positive correlations, blue arrows negative, and gray dashed lines indicate nonsignificant correlations. The numbers on the arrows are standardized path coefficients, and the model includes the proportion of explained variance. Model fit indices are also provided (χ.2, degrees of freedom (df), probability level (P), and root-mean-square error of approximation (RMSEA))

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Spearman’s correlation analysis was used to identify further links between these bacterivorous nematode zOTUs and bacterial zOTUs. We found that these bacterivorous nematode zOTUs were positively correlated with bacterial zOTU 181 belonging to Bacillus spp. (zOTU74: R = 0.81, p = 0.009; zOTU731: R = 0.74, p = 0.02; zOTU241: R = 0.80, p = 0.009; zOTU252: R = 0.96, p < 0.001; zOTU112: R = 0.75, p = 0.002; Fig. 3d). Moreover, a strong negative correlation (R = − 0.70, p = 0.014) was found between the relative abundance of zOTU 181 (Bacillus) and disease incidence based on the data in the field experiment (Fig. 3d). Relative abundance change of zOTU 181 (Bacillus) was the fifth most increased zOTU just after zOTU 65 (Lysinibacillus), zOTU 159 (Nitrosospira), zOTU 102 (Methanomassiliicoccus), and zOTU 67 (Methylobacillus). Structural equation model (SEM) indicated that bacterivorous nematodes could change bacterial community composition (R = 0.588, p < 0.001). Abundances of Bacillus zOTU (zOTU 181) were suggested to be increased by bacterivorous nematodes (R = 0.354, p = 0.024), linked to declines in tomato disease incidence (Bacillus OTU 181: R = − 0.765, p < 0.001, bacterial community composition: R = − 0.662, p < 0.001; Fig. 3e).

Pathogen suppression capability of bacterivorous nematodes (in vitro exp. 1 and greenhouse exp. 1 and 2)

The first in vitro experiment showed that Protorhabditis moved to R. solanacearum immediately after being introduced to nematode growth medium (Fig. S3 and Table S4). After 24 h, the abundance of nematodes in both treatments (Ctrl and + R. solanacearum treatment) was increased by 52.6% and 149.4% compared with the initial inoculation, respectively (Fig. S4). The abundance of nematodes on nematode growth medium cultured with R. solanacearum was 67.2% higher than in Ctrl after 24 h (p < 0.001, unpaired Student’s t-test, Fig. S4).

The first greenhouse experiment estimated the effect of bacterivorous nematodes to decrease plant disease incidence in nematode-free soil. Results showed that although the Protorhabditis density initially inoculated was different, the Protorhabditis density in each treatment was not significantly different when the tomatoes in pots were harvested (Fig. S5a and Table S4). The R. solanacearum density in soils inoculated with 800 Protorhabditis individuals was lowest and was 21.80% lower than Ctrl treatment (Fig. 4a and Table 1). All treatments inoculated with Protorhabditis nematode (Pro1, Pro2, and Pro3) reduced 72.2%, 94.4%, and 77. 8% tomato disease incidence compared to Ctrl treatment, respectively, and no significant difference among treatments inoculated with nematodes (Pro2 and Pro3) was observed (Fig. S5b). A strong negative relationship was found between Protorhabditis nematode density in soils and tomato disease incidence (Fig. 4b). Spearman analysis also showed a negative correlation between Protorhabditis nematode density and R. solanacearum density (Fig. 4c). When sterilized soils were used in the second greenhouse experiment, no significant differences in tomato disease incidence and in the abundance of R. solanacearum were observed between the S_Ctrl treatment and S_P treatment (p > 0.05, unpaired Student’s t-test; Fig. S6 and Table 1).

Fig. 4
figure 4

Pathogen suppression capability of Protorhabditis nematodes in soil. a Effects of different inoculated Protorhabditis nematode abundance on tomato disease incidence. b Correlation between R. solanacearum density Protorhabditis abundances in pots. c Correlation between tomato disease incidence and Protorhabditis abundances in pots. In a and b, p- and R-values were calculated by Spearman’s correlation test, and gray shading denotes 95% confidence intervals. In the Ctrl, no Protorhabditis nematode was inoculated. Pro1, soil inoculated with 200 individuals Protorhabditis nematodes. Pro2, soil inoculated with 400 individuals Protorhabditis nematodes. Pro3, soil inoculated with 800 individuals Protorhabditis nematodes

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Bacterivorous nematodes together with Bacillus reduce Ralstonia solanacearum (in vitro exp. 2–5 and greenhouse exp. 3)

The results in the second in vitro experiment revealed that Protorhabditis could feed on the outer wall of bacterial colonies immediately after being placed on nematode growth medium cultured with each of the tested bacterial strains. Protorhabditis had the weakest predation preference for Bacillus (Fig. 5a and Table 1). The inhibition effect of Bacillus on R. solanacearum was 298.8% higher than the average value of other bacterial strains (Fig. 5b and Table 1). The Spearman correlation analysis showed the negative relationship between predation preference of Protorhabditis to bacteria and the inhibition rate of bacteria to R. solanacearum (Fig. 5c).

Fig. 5
figure 5

Predation preference of Protorhabditis nematodes on different bacterial strains and effects of Protorhabditis nematodes and different bacterial strains antagonizing R. solanacearum. a Predation of nematodes on different bacterial strains; the 0 scale represents the comparison with pathogens as the standard; the lower the value, the less preyed by nematodes or the more preyed by nematodes (n = 12). b Inhibition effects of bacterial strains on R. solanacearum (n = 6). c Correlation between inhibition effects of bacterial strains and predation preferences of Protorhabditis; gray shading denotes 95% confidence intervals. d Inhibition rate to R. solanacearum of cultured supernatant of bacterivorous nematode Protorhabditis, bacterial strains alone, and the combination of strains and nematodes (n = 6). The red dotted line represents the average anti-R. solanacearum ability of nematode culture supernatant. eR. solanacearum density in the absence (Ctrl) or presence of Protorhabditis nematodes, bacterial strains, and combinations of bacterial strains and Protorhabditis (n = 6). The gray and yellow dotted lines represent the average density of R. solanacearum in the Ctrl and + Pro treatments, respectively. Pro, Protorhabditis nematodes; Bac, Bacillus; Pae, Paenibacillus; Lys, Lysinibacillus; Fic, Fictibacillus; Ped, Pedobacter; Mes, Mesorhizobium; Art, Arthrobacter; Mic, Microvirga; and Phy, Phycicoccus. In all panels, boxes with different letters indicate significant differences as defined by one-way ANOVA with Tukey’s post hoc test (p < 0.05). Significant differences in d and e by two‑tailed unpaired t-test (*p < 0.05; **p < 0.01; ***p < 0.001). In d and e, blue lowercase letters mean Tukey test results of the differences in (+ Bacteria) treatments, and yellow uppercase letters mean the Tukey test results of the differences in (+ Bacteria & Pro) treatments

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The result was similar in the third in vitro experiment, when Bacillus was disrupted in the bacillomycin D pathway, as the inhibition rate to R. solanacearum was 50.9% lower than in the WT_Bac treatment. On the contrary, the bacterivorous nematode abundance predation in Mu_Bac treatment was 276.80% higher than in the WT_Bac treatment (Fig. S7 and Table S5).

In the fourth in vitro experiment, the antagonistic ability of bacteria against R. solanacearum after co-cultivation of nematodes and bacteria was investigated. The results showed that the antagonistic ability of the liquid supernatant of Protorhabditis was 49.6%, 28.6%, and 42.7% lower compared to that of Bacillus, Paenibacillus, and Fictibacillus (Fig. 5d and Table 1). The antagonistic ability of liquid supernatants of Bacillus, Fictibacillus, and Lysinibacillus cultured together with Protorhabditis was 54.8%, 63.5%, and 131.2% higher than that of bacteria cultured alone (Fig. 5d and Table 1), and higher than other “bacteria-bacterivorous nematodes” combined treatments (Fig. 5d and Table 1).

In the fifth in vitro experiment, the co-culture experiments of bacteria strains, R. solanacearum, and Protorhabditis nematodes, were carried out to test the synergistic effect of bacterivorous nematodes and bacteria against the pathogen. Results showed that the abundance of R. solanacearum in Ctrl treatment was 44.9% higher than that in the Protorhabditis treatment and each bacterial strain treatment (Phy: 56.1%, Fic: 65.0%, Bac: 67.6%, Art: 60.4%, Mes: 58.0%, Ped: 62.9%, Pae: 56.4%, Mic: 66.5% and Lys: 41.2%; Fig. 5e and Table 1). The abundance of R. solanacearum in Bacillus, Lysinibacillus, and Fictibacillus cultured with Protorhabditis was 87.84%, 61.75%, and 88.51% lower than these in treatments just combined R. solanacearum and bacterial strains (Fig. 5e and Table 1). This finding was similar with results in the third in vitro experiment, indicating that nematodes cooperated with Bacillus produced stronger pathogen suppression ability than other treatments.

According to the fourth and fifth in vitro experiments, we further selected three bacterial strains (Bacillus, Fictibacillus, and Lysinibacillus) for the subsequent third greenhouse experiments. We combined Protorhabditis nematodes with pathogen-antagonistic bacteria: Bacillus, Fictibacillus, and Lysinibacillus, respectively. The results revealed that all bacteria-nematode combined treatments decreased tomato disease incidence (P + Bac: 84.7%; P + Fic: 20.2%; P + Lys: 83.4%, Fig. 6a) compared to the Ctrl treatment. Furthermore, the R. solanacearum density in the P + Bac treatment was 28.0% and 17.2% lower than those in Ctrl and P treatments (Fig. 6b). However, the Protorhabditis density in the P + Bac treatment was 49.4% lower than in the P treatment (Fig. S8 and Table S5). In addition, inoculation of Protorhabditis nematodes increased soil Bacillus densities. Specifically, the Bacillus density in the P treatment and the P + Bac treatment was 18.2% and 22.7% higher than that in the Ctrl treatment (Fig. 6d), which is similar to the first greenhouse experiment (Fig. S9 and Table S6).

Fig. 6
figure 6

Effect of combinations of Protorhabditis and bacteria on tomato health. a Plant disease incidence. b Soil R. solanacearum density. Data are plotted as means ± SEs (n = 3), and bars with different letters indicate significant differences as defined by one-way ANOVA with Tukey’s post hoc test (p < 0.05)

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Discussion

Here, we demonstrated that the synergy of bacterivorous nematodes and pathogen-antagonistic bacteria stimulated by bio-organic fertilizer application changed microbiome composition and functioning that enhanced disease suppression (Fig. 7).

Fig. 7
figure 7

Conceptual model. Conceptual model depicting the mechanisms illustrating how bacterivorous nematodes directly feed on pathogenic bacteria and promote by selective predation of a pathogen-antagonistic microbiome that benefits plant health

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Application of organic fertilizers usually increases the soil organic matter content, which provides a rich source of nutrients for microbial growth [63]. In turn, microbial communities change, with abundances of certain bacteria, fungi, or other microorganisms increasing more than others, while also microbial interactions shift [64]. In our field experiment, we found that bio-organic fertilization increased absolute abundances of nematodes and relative abundances of bacterivorous nematodes, which is in agreement with hypothesis 1. Notably, the bio-organic fertilizer contained a rich organic component compared to the chemical fertilizer. This organic carbon likely is the basis for increased biodiversity gains, especially among nematodes as shown at the local and the global scale [23, 65, 66]. Previous research has demonstrated that the incorporation of carbon-rich materials, such as crop residues based on straw, enhances nematode abundances [67]. Indeed, our findings revealed that bio-organic fertilizers alter soil parameters, particularly within the realm of associated soil organic matter, which leads to changes in both nematode community structure and functional composition [68,69,70]. Prior studies illuminated that bio-organic fertilization establishes a favorable environment for bacteria and thereby their microbiome predatory protists [19]. Nematodes as main bacterial predators have also been shown to be increased with fertilizers [14, 39, 71], which we confirm here.

Predators play a crucial role in shaping ecosystems by controlling prey populations, which in turn affects the entire food web [72, 73]. Predators can also stabilize entire food webs against disturbances [74]. It is remarkable that even microbial predators can shift the balance within soil micro-food webs, showcasing their importance in maintaining ecosystem functionality. Our findings highlighted this insight and confirmed hypothesis 2 that increased relative abundances of bacterivorous nematodes can change microbiome composition and function by favoring pathogen-antagonistic bacteria. Here, we identified the key bacterivorous nematode Protorhabditis that positively affected the relative abundance of pathogen-antagonistic bacteria in soil, such as Bacillus. Previous studies found that bacterivorous nematode communities dominated by Protorhabditis could enhance bacterial abundance and composition in the plant rhizosphere through moderately feeding on bacteria [31]. In our laboratory and greenhouse experiments, we could show that Protorhabditis preferentially preyed on those bacteria with limited pathogen-antagonistic ability, which enhanced the success of pathogen-antagonistic bacteria. It is likely that mechanisms underlying pathogen-suppression equally defend against predation, while other confounding physiological or chemical factors (differences in morphology, biofilm production or differential secondary metabolite production) might play a role [75]. Indeed, certain secondary metabolites confer resistance against protist predation, including violacein, polyketide antibiotics, hydrogen cyanide, the exoprotease AprA, and cyclic lipopeptides [76], which likely also explains different feeding of nematodes on bacteria found here.

Predators tend to select prey that are less well-defended—those that are slower, less camouflaged, or lacking in other defense mechanisms. This selective feeding behavior, driven by the presence or absence of effective prey defenses, demonstrates how predation shapes the evolution of survival strategies in prey populations [77]. This idea is consistent with hypothesis 3, as nematodes reshaped bacterial community with increased pathogen-antagonistic functioning resulting in increased plant health. In our laboratory and greenhouse experiments, Protorhabditis directly preyed on R. solanacearum, thereby likely minimizing their abundance compared to other bacteria in the microbiome [78]. We actually found that pathogen-antagonistic bacteria, such as Bacillus, Lysinibacillus, and Fictibacillus, benefited from the presence of Protorhabditis. Moreover, we showed that the combination of Protorhabditis and Bacillus led to the lowest bacterial wilt disease incidence rather than the application of Protorhabditis or Bacillus alone, supporting former findings that interactions of different players (e.g. organisms, resources) might disproportionally increase soil function compared to single players [79]. Therefore, our findings support the assumption that predator-induced pathogen suppression leads to plant-beneficial side effects [20]. We further confirm that predation by Protorhabditis stimulates the expression of pathogen-antagonistic functions by promoting the production of Bacillus-derived secondary metabolites, resulting in prey shifting to pathogens or other bacteria leading to inhibited pathogen growth. Results from our third greenhouse experiment indicated that the addition of nematodes stimulated densities of indigenous Bacillus in the soil. However, when both nematodes and Bacillus were inoculated together, the density of Bacillus was lower compared to the treatment with only Bacillus inoculation. Despite this, the incidence and abundance of R. solanacearum were lowest in the combined inoculation treatment. These findings support the evolutionary theory that prey tends to enhance their ability to avoid predators under predation [80]. Therefore, we propose that microbial secondary metabolite biosynthesis stimulated by predator pressure induces soil pathogen suppression and enhances plant health.

Our findings can be translated into practical agricultural applications by promoting the use of Protorhabditis nematodes together with already often-applied Bacillus spp. These organisms together might stimulate the individual known function of Bacillus spp. to enhance soil health by fostering beneficial microbial communities and suppressing pathogens, thereby potentially reducing the need for chemical inputs. However, variability in soil types and environmental conditions across regions may affect the efficacy of these bio-organic fertilizers. Moreover, introducing Protorhabditis nematodes and Bacillus spp. into soils may alter overall soil biodiversity, with resulting consequences for other soil functions like nutrient cycling and organic matter decomposition. Further research should focus on these aspects to ensure that the introduction of this combination can actually become a widely used product to positively contribute to a more sustainable agriculture.

Conclusions

In summary, we uncovered the pivotal role of nematode predation on microbiome composition and functioning towards a pathogen-antagonistic microbiome and increased plant health. The finding of the regulatory effect of nematode predation on plant bacterial wilt provides an important advancement to our understanding of plant-pathogen interactions in soils. Our findings demonstrated that nematode microbiome predators should be added to the common microbial-centered studies on the mechanisms and sources of plant bacterial wilt and plant pathogens in general. This work might pave the way for the development of upgraded sustainable agricultural practices that harness beneficial nematodes to naturally control plant diseases, thereby reducing reliance on chemical treatments. Future research could explore the specific interactions between different nematode species and soil microbes to develop targeted biocontrol strategies.

Data availability

All raw sequence data (bacteria and nematode) have been made available in the NCBI Sequence Read Archive (SRA) database under the BioProject PRJNA1029785 and PRJNA1029901.

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Acknowledgements

We thank Prof. Manqiang Liu (Nanjing Agricultural University) for the constructive comments on our initial experiment design. We also thank Nanjing Institute of Vegetable Science for permission to use the field site.

Funding

This research was supported by National Natural Science Foundation of China (42,090,065 and 42,277,294), Fundamental Research Funds for the Central Universities (KJJQ2024020), the Natural Science Foundation of Jiangsu Province, China (BK20210390), Agricultural Science and Technology independent innovation fund project of Jiangsu Province (CX(22)2043), and the Achievement Transformation Fund project of Hainan Research Institute of Nanjing Agricultural University (NAUSY-CG-ZD-01).

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Authors and Affiliations

  1. The Sanya Institute of the Nanjing Agricultural University, Jiangsu Provincial Key Lab for Solid Organic Waste Utilization, Jiangsu Collaborative Innovation Center of Solid Organic Wastes, Educational Ministry Engineering Center of Resource-Saving Fertilizers, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China

    Xu Xu, Renqiang Jiang, Xinling Wang, Shanshan Liu, Hancheng Mao, Xingrui Li, Ziyu Ni, Nana Lv, Xuhui Deng, Wu Xiong, Chengyuan Tao, Rong Li & Qirong Shen

  2. Ecology and Biodiversity Group, Department of Biology, Institute of Environmental Biology, Utrecht University, Padualaan 8, 3584 CH, Utrecht, The Netherlands

    Shanshan Liu

  3. Department of Agroecology, Faculty of Technical Sciences, Aarhus University, Forsøgsvej 1, 4200, Slagelse, Denmark

    Menghui Dong

  4. Laboratory of Nematology, Wageningen University, 6700 AA, Wageningen, The Netherlands

    Stefan Geisen

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  1. Xu Xu
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Contributions

X.X., R.L., C.T., W.X. and S.G. wrote the manuscript. X.X., R.L., S.G., S.L., M.D., X.D., C.T. and Q.S. developed the ideas and designed the experimental plans. X.X., R.J., X.W., X.L., H.M., Z.N. and N.L. performed the experiments. X.X., R.L., W.X. and S.G. analyzed the data. All authors reviewed the manuscript.

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Correspondence to Chengyuan Tao or Rong Li.

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Xu, X., Jiang, R., Wang, X. et al. Protorhabditis nematodes and pathogen-antagonistic bacteria interactively promote plant health. Microbiome 12, 221 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s40168-024-01947-1

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Keywords

Microbiome

ISSN: 2049-2618

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