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Differential responses of root and leaf-associated microbiota to continuous monocultures

Environmental Microbiome volume 20, Article number: 13 (2025) Cite this article

Abstract

Continuous monocultures alter the composition and function of root-associated microbiota, and thus compromise crop health and productivity. In comparison, little is known about how leaf-associated microbiota respond to continuous monocultures. Here, we profiled root and leaf-associated microbiota of peanut plants under monocropping and rotation conditions. Additionally, their protective effects against root pathogen Fusarium oxysporum and leaf pathogen Alternaria alstroemeriae were evaluated. We found that monocropping increased root and leaf disease severity. Meanwhile, the peanut growth and productivity were inhibited by monocropping. Microbiota analysis revealed that monocropping reduced rhizosphere microbial population and diversity, while increased leaf epiphytic microbial population and did not influence leaf epiphytic microbial diversity. Cropping conditions had a greater impact on the microbiota composition of leaf epiphytes than that of the rhizosphere. Moreover, in vitro and in vivo experiments, combined with correlation analyses showed that monocropping weakened the antagonistic activity of rhizosphere microbiota against F. oxysporum and root rot disease. This effect may be associated with the depletion of Bacillus sp. and Sphingomonas sp.. By contrast, leaf epiphytic microbiota under monocropping exhibited greater inhibition of A. alstroemeriae growth and leaf spot control. Together, our results demonstrated a differential response pattern of root and leaf-associated microbiota to continuous monocultures.

Introduction

Plant-associated microbiota are key contributors to host nutrient uptake, stress adaptation, and resistance to pathogens [1,2,3,4]. Previous studies have indicated that agricultural practices can modulate plant growth, health, and productivity by influencing the composition and function of the plant-associated microbiota [5]. For example, in a comparison of crops grown under continuous monoculture and rotation conditions, it is shown that the former has higher pathogenic microbial abundance in the rhizosphere and greater disease severity, which thus compromises plant health and productivity [6]. It is established that the enrichment of soil-borne pathogens and the outbreaks of pathogenic diseases under continuous monoculture conditions are attributed to the gradual loss of antagonistic microbes, for instance Bacillus sp. and Streptomyces sp., and the continuous release of the same types of root exudates and litters [7, 8]. Such negative effects can be alleviated by crop rotation through the accumulation of Arbuscular mycorrhizal fungi (AMF) and rhizobia in the rhizosphere [9, 10]. In contrast to the intensively studied roles of root-colonizing microbiota in crop health under different agricultural practices, our understanding of how agricultural practices affect leaf-associated microbiota remains limited.

The phyllosphere, including the aerial parts of plants, is dominated by the leaves. Phyllosphere microbes contribute to plant growth, development, immunity, productivity, and ecosystem function [11,12,13,14]. For instance, phyllosphere microbes promote plant growth through 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase production and nutrient cycling enhancement [15]. Moreover, the eubiosis of the phyllosphere microbiota is important to plant health. For example, the dysbiosis of Firmicutes and Proteobacteria in the phyllosphere results in leaf necrosis and chlorosis [11]. An ecological study examined phyllosphere microbiota across experimental forest plots and found a positive correlation between leaf bacterial diversity and terrestrial ecosystem productivity [13]. Like the rhizosphere, the phyllosphere is inhabited by a diverse microbiota, with some microbes living on the surface of plants as epiphytes and others residing inside leaves as endophytes. In general, the leaf epiphytic surfaces show higher microbial diversity and function compared to the leaf endosphere compartment [14]. It is estimated that over 99% of total leaf-associated bacterial microbiota is colonized in the leaf surfaces of Arabidopsis [11]. Moreover, like the rhizosphere, leaf surface-colonized microbiota is the first line that defends against pathogen invasion [6, 16]. Considering the importance of leaf-associated microbiota in plant growth, development, immunity, and productivity, uncovering how agricultural practices influence leaf-associated microbiota is of considerable research significance.

Leaf-associated microbiota can be derived from multiple sources, including soil, seeds, and air, and the soil has been suggested as the major source of microorganisms detected in the phyllosphere [17, 18]. Consequently, the phyllosphere and rhizosphere have substantial overlap in microbiota composition. For instance, root-colonizing bacteria such as Streptomyces sp. can translocate endophytically to stem and flower via the vascular bundle [19]. Despite the similarity in phyllosphere and rhizosphere microbiota, increasing studies have suggested the filtering effects of plant organs on their associated microbiota [8]. Such filtering effects are mediated by the structure and chemistry of plant organs, and the natural factors, such as wind, rain, and insects [20]. For example, compared to roots, leaves have a larger apoplast, which facilitates the gas exchange or photosynthesis and can provide a larger air-filled internal space for microbiota colonization [11]. Moreover, the differences in resource availability between phyllosphere and rhizosphere environments also contribute to the variations in the compositions of their microbiota [14]. Agricultural practices have been reported to alter plant phenotype and metabolism [5], we thus hypothesized that the leaf and root-associated microbiota respond to monoculture and rotation in a nonparallel way.

To test this hypothesis, a combination of field trials and pot experiments with peanut plants grown under monoculture and rotated conditions was conducted to (1) analyze the effects of monocropping (MP) and rotation (RP) on leaf and root disease severity, (2) profile and compare rhizosphere and leaf epiphytic microbiota, and (3) analyze the antagonistic activities of rhizosphere and leaf epiphytic microbiota against fungal pathogens.

Materials and methods

Plant and microbial materials

Peanut seeds (Ganhua-5) were obtained from the Ecological Experimental Station of Red Soil, Chinese Academy of Sciences (Yintan, Jiangxi Province, China; 28°130′N, 116°550′E). Seeds were sorted for uniformity, and then surface-disinfected with 70% (v/v) ethanol for 5 min, 3% (v/v) sodium hypochlorite for 3 min and washed three times with sterile water. The Alternaria alstroemeriae BD1 was obtained from the Institute of Soil Science, Chinese Academy of Sciences (Nanjing, Jiangsu Province, China). The Fusarium oxysporum was obtained from the Jiangsu Key Laboratory for Pathogens and Ecosystems of Nanjing Normal University (Nanjing, Jiangsu Province, China). Both A. alstroemeriae BD1 and F. oxysporum were previously isolated from the leaves and roots of diseased peanut plants, respectively [21, 22].

Field and pot experimental designs

The field trial and pot experiments were conducted at the Botanical Garden of Nanjing Normal University (Jiangsu Province, China; 32°11′N, 118°91′E). The field experiment contained two different cultivation regimes: (1) peanut monocropping regime (MP) and (2) maize and peanut rotation regime (RP). The design of the field experiment was described in the previous study [9]. The field was split into eight plots in the fall of 2017. The plots in the field experiment were set up in a randomized complete block design. Each regime consisted of four plots and each plot was 5 × 4 m (length × width). For the MP regime, the plots were continuously grown with peanut (Ganhua-5) for six years (2017–2022). For the RP regime, the plots were cultivated with peanut in 2018, 2020, and 2022, and cultivated with maize in 2017, 2019, and 2021 (Fig. 1). The peanut was sown in May and harvested in September. At harvest, the shoot and root straw of peanuts were removed from the field. In 2022, the peanut root rot and leaf spot disease severity in MP plots were higher than those in RP plots at flowering stage (Fig. S1).

Fig. 1
figure 1

Schematic diagram of the key experimental arrangements in this study. The field trial consisted of two different cultivation regimes: (1) peanut under a monoculture regime and (2) maize and peanut under a rotated regime. The soils (0–20 cm) were collected from the field trial and used for the pot experiment. The plant growth parameters, rhizosphere and leaf epiphytic microbiota, and antagonistic activity of bacterial communities against pathogens were determined

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Pot experiment set up

For pot experiment, the soils (0–20 cm) were collected from each plot in April at 2023 before the field trial. For each plot, four pots (28 cm diameter, 22 cm height) were established. Thus, the pot experiment included 32 pots, and each treatment contained 16 pots (Fig. 1). Four pots (one pot from each plot) from each treatment were used for shoot height, root length, shoot dry weight and root dry weight determination. Eight pots (two pots from each plot) from each treatment were used for root nodule-related parameter, leaf spot disease, root rot disease, and rhizosphere and leaf epiphytic microbiome analyses. The remaining 4 pots (one pot from each plot) from each treatment were used for pod yield determination. Each pot was planted with three peanuts. The pots were maintained in a greenhouse (28 ± 2 °C, 16:8 h light/dark, with 55 ± 5% relative humidity). The physicochemical properties of the soil for the pot experiment were provided in a previous study [8]. The peanuts were watered with sterile water every five days.

Plant growth parameters and disease index determination

At the early flowering stage (45 days after sowing), the peanut plants were sampled from 4 plots (one pot from each plot) each treatment for growth parameters (shoot height, root length, and biomass), and the disease severity was determined. The number of root tips was determined using a root scanner (ScanMaker i800 Plus, Microtek, Shanghai, China). The severity of leaf spot and root rot was evaluated as [Σ(ni × vi)/(V × N)] × 100%, where ni is the number of plants with the respective disease rating, vi is the disease rating, V is the highest disease rating (here, V = 5), and N is the total number of observed plants. The disease ratings for leaf spot were evaluated based on the percentage of diseased leaf area using six-class rating scale (0 = no disease, 1 = 1% < vi ≤ 10%, 2 = 10% < vi ≤ 20%, 3 = 20% < vi ≤ 30%, 4 = 30% < vi ≤ 40%, 5 = vi > 40%) [23]. Roots were rated for root rot symptoms following a six class rating scale based on percentage discoloration of the roots (0 = no disease, 1 = 1% < vi ≤ 25%, 2 = 26% < vi ≤ 50%, 3 = 51% < vi ≤ 75%, 4 = 76% < vi ≤ 100%, 5 = dead plant) [24].

Rhizosphere and leaf epiphytic samples collection

At the early flowering stage (45 days after sowing), the rhizosphere soil and leaf samples were collected from MP and RP treatments in pot experiment. The rhizosphere soil samples were collected by brushing the soil adhering to the roots. The procedure to collect leaf epiphytic microbiota was according to [25] with some modifications. Briefly, the third fully expanded leaves on the main stem (termed functional leaf) in peanuts were collected [26]. The leaf tissues were first transferred into a 250-ml conical flask containing 200 ml sterile phosphate-buffer saline (PBS, 4 °C), and then subjected to sonication for 1 min and shaking at 180 rpm for 1 h at 20 °C to dislodge the epiphytic microbes from leaf surface into PBS. The PBS solution was centrifuged at 4500 g for 20 min at 4 °C, and the precipitates were collected as leaf epiphytic samples. Half of the samples were used for microbiota analysis, and the rest were used for the determination of 16S rRNA gene copy number and antagonistic activity.

Determination of bacterial abundance in rhizosphere and leaf epiphytic samples by quantitative real-time PCR

Quantitative real-time PCR was used for the quantification of total bacteria in the rhizosphere and leaf epiphytic samples. Briefly, the DNA of rhizosphere and leaf epiphytic samples was extracted with a FastDNA SPIN Kit (MP Biomedicals, Santa Ana, CA, USA). DNA integrity and concentration were determined by agarose gel electrophoresis and a NanoDrop spectrophotometer (Thermo Scientific, Waltham, MA, USA), respectively. The abundance of bacteria was quantified using Eub338F, 5′-ACTCCTACGGGAGGCAGCAG-3′, and Eub518R, 5′-ATTACCGCGGCTGCTGG-3′ [27]. The reaction system contained 7 µL of double-distilled H2O, 10 µL of 2 × SYBR Green master mix (Vazyme, Nanjing, China), 0.5 µL each primer (10 µM), and 2 µL of template DNA. The PCR procedure was as follows: 95 °C for 30 s; and 38 cycles of 95 °C for 5 s, 57 °C for 60 s, and 72 °C for 60 s. Each samples was analyzed in eight replicates. The standard curve was generated by plotting the threshold cycle (Ct) values of the three replicates versus the logarithm of known concentration of ten-fold dilution of a plasmid containing a full-length copy of 16S rRNA gene from Escherichia coli.

DNA extraction, 16S rRNA gene sequencing, and bioinformatic analysis

The DNA of rhizosphere and leaf epiphytic samples was extracted with a FastDNA SPIN Kit (MP Biomedicals, Santa Ana, CA, USA). DNA integrity and concentration were determined by agarose gel electrophoresis and a NanoDrop spectrophotometer (Thermo Scientific, Waltham, MA, USA), respectively. The amplicon libraries were prepared using universal primers 799F (5′-AAC MGG ATT AGA TAC CCK G-3′) and 1193R (5′-ACG TCA TCC CCA CCT TCC-3′), as these primers help to avoid amplification of chloroplasts and other plant-associated DNA sequences [16]. Each sample was amplified in a 20 µl reaction system. The reaction system included 1 × Premix Taq DNA polymerase (Takara, Kusatsu Japan), 20 ng of DNA templates, and 0.5 µM forward and reverse primers. The amplification was carried out with the following conditions: initial denaturation at 95 °C for 3 min, 30 cycles of denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s, and extension at 72 °C for 5 min, followed by a final extension at 72 °C for 1 min. Amplicon sequencing libraries were constructed using the MiSeq Reagent Kit v3. Paired-end 300-bp reads were sequenced by Majorbio Bio-Pharm Technology Co. Ltd (Shanghai, China) on an MiSeq platform (Illumina, San Diego, CA, USA) according to the manufacturer’s instructions. Denoising was performed with the DADA2 module within the QIIME2 environment [28]. After sequencing denoising, dereplication, chimera filtering and removing non-specific reads, the remaining sequences were binned into operational taxonomic units (OTUs) with a 97% nucleotide similarity threshold using UPARSE (version 11) pipeline [29]. Each OTU was taxonomically classified using the RDP classifier (version 2.13). ACE, Chao1 estimator, Shannon index, and Simpson index were used to compare the alpha diversity among treatments. A principal coordinate analysis (PCoA) based on Bray–Curtis dissimilarity was performed to explore patterns of microbial community composition using the Vegan package (v2.5-6) [30]. Differences in microbial community composition across treatments were determined with permutational multivariate analysis of variance (PERMANOVA, permutation = 999) using the adonis function from the R package. The functional Annotation of Prokaryotic Taxa (FAPROTAX) v.1.2.1 [31]. The raw sequencing data were deposited using the SRA service of the GenBank database under the accession number PRJNA1131189.

Antagonistic activity of rhizosphere and leaf epiphytic microbiota against F. oxysporum and A. alstroemeriae

To prepare rhizosphere and leaf epiphytic microbiota, 2 g (dry weight equivalent) of fresh rhizosphere soil and leaf epiphytic samples were added to 18 ml of sterile water and mixed on a rotary shaker (Zhichu Biotechnology Co., Ltd, Shanghai, China) at 180 rpm at 4 °C for 2 h [32]. The soil and leaf epiphytic suspensions were then sonicated for 1 min at 60 kHz using a sonicator (Scientz Biotechnology Co., Ltd, Ningbo, China), and mixed again for 0.5 h. The suspensions were filtered through a 5-μm filter to remove a large proportion of fungal propagules [33]. A 100 μl of the prepared suspensions (soil and leaf epiphyte) was spread on an LB-agar medium. A half-strength sterile PDA medium with 50 mg L−1 of streptomycin to inhibit bacterial growth was prepared as the lid. A fungal plug (5-mm diameter) was then inoculated in the center of the half-strength sterile PDA medium. The elongation of fungal hyphae was determined after 5 days of co-culture. The radial growth of A. alternata and F. oxysporum was determined by calculating the distance from four equidistant points from the center of the plug to the colony edge. Four replicates were analyzed for the soil from each plot, with three replicates of each treatment.

A 50 μl of soil or leaf epiphytic suspensions were inoculated on a piece of sterile cellulose filter (1 cm × 6 cm) placed on one side of the nutrient-agar (NA) medium. An A. alstroemeriae or F. oxysporum plug was then inoculated on the medium 2 cm away from the cellulose filter. The plate was then sealed with Parafilm and incubated at 28 °C. After cultivation for 4 days in the dark, the elongation of fungal hyphae was determined. The radial growth of A. alstroemeriae and F. oxysporum was determined by calculating the distance from the center of the plug to the cellulose filter. The treatments were performed in four biological replicates and three technical replicates of each treatment.

Control of rhizosphere and leaf epiphytic microbiota against root rot and leaf spot

Surface disinfected peanut seeds were sown in vermiculite and maintained in a growth chamber (28 ± 2 °C, 14 h light/10 h dark photoperoid) for two weeks. The peanut seedlings were washed with sterile water to remove vermiculite and maintained in Petri dishes. Each seedling root was inoculated with 200 µl of microbiota suspension from MP and RP rhizosphere. The seedling root was then inoculated with two medium blocks (0.5-cm-diameter) containing 7-day-old F. oxysporum mycelia. The inoculation site was wrapped with absorbent paper soaked with sterile water [34]. The Petri dishes were maintained in a growth chamber at 28 ± 2 °C, 14 h light/10 h dark photoperiod. The length of the root lesion was recorded 5 days after inoculation. The experiment was performed in four individual replicates.

Surface-disinfected peanut seeds were sown in vermiculite and maintained in a growth chamber (28 ± 2 °C, 14 h light/10 h dark photoperiod) for four weeks. The third fully expanded leaves of plants were sampled and maintained in Petri dishes. Each leaf was sprayed with 200 µl of microbiota suspension from MP and RP leaf epiphyte. The leaf was then inoculated with a medium block (0.5 cm diameter) containing 7-day-old A. alstroemeriae mycelia. The length of the root lesion was recorded 7 days after inoculation. The experiment was performed in four individual replicates.

Nodule histological observation

At the early flowering stage (45 days after sowing), the nodules were collected and fixed in a mixture of 2.5% glutaraldehyde and 4% paraformaldehyde in 0.1 M sodium cacodylate (pH 7.2) [35]. Fifteen representative nodules from three different plants of MP and RP treatments were fixed. The fixed nodules were then dehydrated by a series of ethanol and embedded in paraffin. Thin sections (5 µm) were stained with safranine O-fast green and observed with a light microscope. The area of the nodular nitrogen fixation zone was determined using ImageJ software (National Institutes of Health, Bethesda, MD, USA).

Statistical analysis

All experiments were performed at least four individual replicates. The data were presented as the mean with standard error (SE). Unless otherwise stated, statistical tests were carried out with SPSS software (v.18.0; SPSS Inc., Chicago, IL, USA). Significant differences were analyzed by either Student’s t-test (*P < 0.05; **P < 0.01; ***P < 0.001) or one-way ANOVA followed by Tukey’s multiple comparison (P < 0.05). Correlations between bacterial abundance and leaf spot or root rot severity were used by Pearson correlation analysis.

Results

MP reduces peanut growth, increases leaf and root diseases

Compared with the rotated conditions, the plant shoot height, and the dry weight of root and shoot were significantly reduced when peanuts were cultivated with monocropped soils at the early flowering stage (45 days after sowing) (Fig. 2a). However, the roots of monocropped peanuts were significant longer than those of rotated peanuts (Fig. 2a, b). No significant difference in root tip number was observed between monocropped and rotated peanuts (Fig. 2b), indicating that monocropped and rotated peanuts have similar lateral root formation.

Fig. 2
figure 2

Plant growth parameters determination. a Effects of monocropping and rotation on peanut shoot height, root length, shoot dry weight, and root dry weight. b Effects of monocropping and rotation on the number of peanut root tips. c Effects of monocropping and rotation on root nodule number and nodule structure. d, e Effects of monocropping and rotation on leaf spot and root rot disease severity. f Effects of monocropping and rotation on pod number and yield at harvest. Data are presented as the mean ± SEM (n = 4). The asterisk indicates a significant difference between monocropped and rotated treatments according to Student’s t-test (*P < 0.05; **P < 0.01; ***P < 0.001). MP, monocropping; RP, rotation; ns, no significance

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The peanut root nodule formation was remarkably inhibited when peanuts were cultivated in monocropped soils (Fig. 2c). After semithin nodule sections were stained with safranine O-fast green, light microscopy observations found that the monocropped and rotated peanut showed similar nodule size, organization patterns, a central N2-fixation zone, vascular bundles surrounded by nodule cortex (Fig. 2c). Additionally, MP did not affect the size of the nodular nitrogen fixation zone (Fig. 2c). Severe root rot and leaf spot disease were found in monocropped peanuts, with the disease index of up to 4.00 and 2.23 fold-change, respectively, compared to rotated peanuts (Fig. 2d, e). At harvest (110 days after sowing), MP reduced the pod number and yield of peanut plants, while it did not affect the weight of a single pod (Fig. 2f, Fig. S2). Together, these results suggest that peanuts grown under MP conditions are suffered from replanting obstacle.

Comparison of rhizosphere and leaf epiphytic microbial communities of MP and RP peanut plants

Compared to RP, MP showed declines in bacterial 16S rRNA gene copies, abundance-based coverage estimator (ACE), and the observed species (Sobs) in the rhizosphere, whereas it increased bacterial 16S rRNA gene copies, ACE, and Sobs in leaf epiphyte (Fig. 3a–c). In terms of bacterial diversity, MP reduced the Shannon index in the peanut rhizosphere but did not affect the Shannon index in leaf epiphyte when compared with RP (Fig. 3d). In addition, the bacterial richness and diversity in rhizosphere soil is higher than those in leaf epiphyte (Fig. 3d).

Fig. 3
figure 3

Rhizosphere and leaf epiphytic microbiota of peanut plants under monocropped and rotated conditions. a The number of 16S rRNA gene copy in MPR, RPR, MPL, and RPL samples. Data are presented as the mean ± SEM (n = 8). The asterisk indicates a significant difference between monocropped and rotated treatments according to Student’s t-test (*P < 0.05; ***P < 0.001). b–d Bacterial ACE, Sobs, and Shannon index in MPR, RPR, MPL, and RPL samples. Data are presented as the mean ± SEM (n = 4). The asterisk indicates a significant difference between monocropped and rotated treatments according to Student’s t test (*P < 0.05; **P < 0.01). e PCoA (based on the relative abundance of bacterial OTUs) of Bray–Curtis distances of MPR, RPR, MPL, and RPL samples. PERMANOVA was performed using the adonis function from the R package. Different letters indicate significant differences among samples (*P < 0.05, one-way analysis of variance followed by Tukey’s honest significant difference test). ACE, abundance-based coverage estimator; Sobs, observed species; MPR, monocropped rhizosphere; RPR, rotated rhizosphere; MPL, monocropped leaf epiphyte; RPL, rotated leaf epiphyte; PERMANOVA, permutational multivariate analysis of variance; ns, no significance

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PCoA analysis revealed that cropping conditions significantly affected the overall structure of bacterial communities in the peanut rhizosphere and phyllosphere (Adonis, R2 = 0.82, P = 0.001) (Fig. 3e, Fig. S3). Meanwhile, the effect of cropping conditions on leaf epiphytic microbiota was greater than that on rhizosphere microbiota (Fig. 3e). Inspection of rhizosphere and leaf epiphytic samples indicated that the bacterial community in these two groups was separated, irrespective of cropping conditions (Fig. 3e), which indicates the influences of root and leaf on their associated microbiome.

Effects of MP and RP on rhizosphere and leaf epiphytic microbial composition

Rhizosphere and leaf epiphytic microbiota under MP and RP conditions harbored different bacterial phyla. The Chloroflexi, Actinobacteriota, Proteobacteria, Acidobacteriota, and Firmicutes were the top five major bacterial taxa at the phylum level in the rhizosphere microbiota (Fig. 4a). MP significantly increased the abundance of Chloroflexi but significantly reduced the abundance of Actinobacteriota, Proteobacteria, Acidobacteriota, and Firmicutes in the rhizosphere (Fig. 4a, Table S1). When comparing the leaf epiphytic microbiota, we found that MP significantly increased the abundance of Actinobacteriota, compared to RP (Fig. 4b, Table S2).

Fig. 4
figure 4

Relative abundances of rhizosphere and leaf epiphytic bacterial phyla (a, b), and Venn diagrams showing compositional differences in the bacterial communities at the OTU level (c). “Others” refers to phyla with a relative abundance below 0.1%. MPR, monocropped rhizosphere; RPR, rotated rhizosphere; MPL, monocropped leaf epiphyte; RPL, rotated leaf epiphyte

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To further probe into the differences in microbial features between root and leaf under MP and RP conditions, we analyzed the rhizosphere and leaf epiphytic microbiota at the OTU level. A 50.53% of OTUs were detected in monocropped and rotated rhizosphere, while only 13.09% were shared between monocropped and rotated leaf epiphyte (Fig. 4c). In addition, rhizosphere and leaf epiphyte shared more overlapping OTUs under MP condition than under RP conditions (Fig. 4c).

In the top 30 bacterial genera, the Bacillus sp. and Sphingomonas sp., which commonly exhibit antifungal activity and promote plant growth, were depleted in the rhizosphere under MP compared to RP conditions (Fig. 5a). Consistently, the abundance of Bacillus and Sphingomonas was negatively correlated with root disease severity (Table S3). Most of the top 30 bacterial genera were enriched in the leaf epiphytes under MP conditions (Fig. 5b). Correlation analyses found that the abundance of Aureimonas, norank_f__norank_o__B12-WMSP1, norank_f__Neisseriaceae, Roseomonas, norank_f__norank_o__Saccharimonadales, Pseudokineococcus, Hymenobacter and Ellin6055 were positively correlated with the leaf disease severity (Table S4). Taken together, these results suggest that root and leaf shared different associated microbiota, irrespective of cropping conditions.

Fig. 5
figure 5

Heatmap of bacterial distribution of the top 30 most abundant genera present in the rhizosphere (a) and leaf epiphyte (b) of peanut plants under monocropped and rotated conditions. Hierarchical clustering analysis was performed using the neighbor-joining method. Differential relative abundance with statistically significant P values is shown (Student’s t-test, P < 0.05)

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Suppression of the pathogens by the rhizosphere and leaf epiphytic bacterial communities in vitro and in vivo

To compare the antagonistic activities of root and leaf-associated microbial communities against peanut fungal pathogens, we extracted bacterial suspensions of rhizosphere soil and leaf epiphytes of peanuts grown under MP and RP conditions, and tested their ability to suppress the root rot pathogen F. oxysporum and leaf spot pathogen A. alstroemeriae in vitro and in vivo. Regardless of indirect or direct antagonistic tests of bacterial suspensions against pathogens, the bacterial suspensions from the rhizosphere soil of RP conditions significantly suppressed mycelial elongation of F. oxysporum and A. alstroemeriae, compared with those obtained from MP (Fig. 6a). Meanwhile, the rhizosphere microbiota under MP conditions did not influence the growth of F. oxysporum in indirect antagonistic tests (Fig. 6a). The bacterial suspensions from the leaf epiphytes of both MP and RP had a stronger suppressive effect on F. oxysporum and A. alstroemeriae growth than the control (Fig. 6b). Contrary to the rhizosphere, the leaf epiphytic microbiota of MP showed a stronger indirect antagonism against F. oxysporum and a stronger direct antagonism against A. alstroemeriae (Fig. 6b).

Fig. 6
figure 6

Effects of bacterial communities from MPR, RPR, MPL, and RPL samples on the growth of F. oxysporum and A. alstroemeriae, and the development of root rot and leaf spot. a Effects of bacterial communities from MPR, RPR, MPL, and RPL samples on the growth of F. oxysporum. Data are presented as the mean ± SEM (n = 6). The asterisk indicates a significant difference between monocropped and rotated treatments according to the Student’s t-test (*P < 0.05; ***P < 0.001). b Effects of bacterial communities from MPR, RPR, MPL, and RPL samples on the growth of A. alstroemeriae. Data are presented as the mean ± SEM (n = 6). The asterisk indicates a significant difference between monocropped and rotated treatments according to Student’s t test (*P < 0.05; **P < 0.01; ***P < 0.001). c Effects of bacterial communities from MPR and RPR samples on the development of root rot caused by F. oxysporum. Data are presented as the mean ± SEM (n = 4). The asterisk indicates a significant difference between monocropped and rotated treatments according to Student’s t-test (*P < 0.05; ***P < 0.001). d Effects of bacterial communities from MPL and RPL samples on the development of leaf spot caused by A. alstroemeriae. Data are presented as the mean ± SEM (n = 4). The asterisk indicates a significant difference between monocropped and rotated treatments according to Student’s t-test (*P < 0.05; **P < 0.01). MPR, monocropped rhizosphere; RPR, rotated rhizosphere; MPL, monocropped leaf epiphyte; RPL, rotated leaf epiphyte; Fo, Fusarium oxysporum; Aa, Alternaria alstroemeriae; ns, no significance; n.d., no detected

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When testing the ability of microbial suspensions to control root rot and leaf disease in vivo, we observed that the bacterial suspensions from the rhizosphere soil of both MP and RP reduced the severity of root rot caused by F. oxysporum, with reductions of 39.34% and 68.13%, respectively, compared to the control (Fig. 6c). Meanwhile, the rhizosphere microbiota from RP conditions reduced the root rot severity by 47.46% as compared to those from MP conditions (Fig. 6c). Similarly, the bacterial suspensions from the leaf epiphytes of both MP and RP reduced the length of leaf lesions caused by A. alstroemeriae, with reductions of 89.58% and 78.33%, respectively, compared to the control (Fig. 6d). Meanwhile, the leaf epiphytic microbiota from MP showed a greater reduction in leaf spot severity, with leaf lesion length reduction of 51.92%, compared to those from RP (Fig. 6d). No disease symptoms were found on un-inoculated roots or leaves (Fig. 6c, d).

Discussion

The outbreak of soil-borne diseases caused by the depletion of beneficial microbes in the root-associated microbial community is a key factor in the replanting obstacle [5, 8]. Unlike roots, which are the direct organs that sense the soil environment, leaves, as photosynthetic organs, develop aboveground. Therefore, how the leaf-associated microbiota changes under the replanting obstacle and whether the knowledge obtained from roots could extend to the leaves are largely unknown. Here, we profiled the changes in rhizosphere and leaf epiphytic microbiota between monocropped and rotated conditions, and underscored the different responses in the composition and function of root and leaf-associated microbiota to cropping regimes.

Consistent with other studies [8, 36], continuous monocropping compromised plant health and reduced plant growth and productivity. This could be due to the soil degradation [7, 37], a shortage of symbiotic nitrogen fixation [36], and the outbreak of soil-borne diseases [8, 10, 38, 39]. Soil degradation, such as the loss of soil fertility and alterations in soil structure, can reduce root growth and leaf photosynthetic activity [40]. The efficiency of symbiotic nitrogen fixation is determined by root structure, rhizobium abundance, and nutritional status and defense of host plants [41,42,43]. In terms of peanuts, the crack sites between cells in the epidermis that originate from lateral roots are the infection sites for rhizobium [42], which is different from the model legume, Medicago truncatula [44]. Thus, the number of lateral roots is a key determinant of nodule formation in peanuts [42]. Peanut has a typical dicotyledonous system with a single taproot branched by the formation of first-, second-, and third-order lateral roots [45]. The number of peanut lateral root can be reflected by the amount of root tips. The root structure and rhizosphere soil microbiome analyses revealed that the number of lateral roots and the abundance of Bradyrhizobium sp. were similar in MPR and RPR. Moreover, the FAPROTAX analysis showed that the potential function related to nitrogen fixation was more abundant in MPR, compare to RPR (Fig. S4). These data suggested that the number of lateral root and abundance of Bradyrhizobium sp. were not the factors for the declines in nodule number under MP conditions. We thus speculate that the nutritional status and defense of host plants contribute to the shortage of symbiotic nitrogen fixation [36, 42]. Consistently, the shoot height and dry weight were reduced in MP, which could negatively influence leaf photosynthetic carbon activity and reduce the energy available for nodulation. In addition, the outbreak of soil-borne diseases resulted in the activation of plant defense, which did not favor the root invasion of rhizobium, as the suppression of plant defenses is a prerequisite for rhizobial invasion [46, 47].

Leaf and root harbor different microbial communities, irrespective of cropping conditions, which indicates a specificity of plant organs for their surrounding microbiota. Three reasons are proposed to explain why the composition of leaf and root-associated microbial communities is different. First, leaves and roots share different growth environments, thus the sources of their associated microbiota are different. Leaf-associated microbiota are derived from multiple sources, including soil, seeds, and air [14, 20, 48]. Meanwhile, the composition of leaf-associated microbiota can also be influenced by natural events, such as wind, rain, and insect visitors [48]. In addition, the leaf surface is subjected to a range of physicochemical stresses, such as high light, ultraviolet (UV) radiation, and fluctuating temperatures [48]. Thus, leaf-associated microbiota are also shaped by such stresses. By contrast, rhizosphere microbiota are sourced from bulk soil, and are influenced by soil nutrients and physiological properties, and host plants [3]. Second, roots and leaves have their own unique morphological and physicochemical properties, which can also impact leaf and root-associated microbial communities. The leaf cuticles and trichomes can be structural niches that are potentially habitable by microbes [49]. The root system contains different types of primary, secondary, and tertiary roots [49], thus the roots can create more ecological niches on their surface for diverse microbial species than leaves. Third, roots and leaves harbor different exudate compositions. It is well known that root exudates, such as sugars, amino acids, flavonoids, and alkaloids, are the main drivers of rhizosphere microbiota assembly [50,51,52]. Compared to the rhizosphere, the leaf surface is a relatively nutrient-poor environment [20]. Consistently, our results indicated that the diversity and load of rhizosphere microbiota were higher than those of leaf epiphyte microbiota, irrespective of cropping conditions.

We observed that the changes in the population, diversity and antifungal activity of leaf and root-associated microbiota due to cropping conditions were different. MP reduced the population and diversity of rhizosphere microbiota, which is due to the continuous release of the same types of root exudates and litters [5, 6]. By contrast, MP increased the population and did not affect the diversity of leaf epiphytic microbiota. We proposed two reasons that could explain why MP increased the population and did not affect the diversity of leaf epiphytic microbiota. First, MP reduced the height of the shoot, which increased the opportunity for rhizosphere microbiota to reach the leaf epiphyte. Consistently, more overlapping OTUs were shared by rhizosphere and leaf epiphytes under MP conditions. Second, leaves may employ the “cry for help” strategy to enhance their ability to combat pathogens under MP conditions. Under pathogen challenges, plants actively seek cooperation with specific microbial genera to maintain plant health [53,54,55]. Consistently, the leaf epiphytic microbiota under MP conditions showed stronger antagonistic activity against fungal pathogens. However, the function of leaf-coloinizing microbiota has been less studied [14]. The negative correlation between leaf.

spot and the enriched genera, such as Aureimonas, and the stronger antagonistic activity of leaf epiphytic microbiota against A. alstroemeriae and leaf spot, led us to speculate that the enriched microbiota in MP leaf epiphytes can directly inhibit A. alstroemeriae growth. Further studies using microbiological culturable and bacterial-fungal confrontation approaches are required to dissect the specific genera recruited by leaves to cope with pathogen attacks.

The depletion of Bacillus sp. and Sphingomonas sp. may be the cause of the reduced antagonistic activity against pathogens under MP. The Bacillus sp. is one of the most exploited microbial genus that inhibit fungal pathogen growth [56,57,58,59,60]. Additionally, Bacillus sp. has been reported to trigger plant defense systems to inhibit pathogen infection [8]. The Sphingomonas sp. also plays a beneficial role in the biological control of plant diseases caused by pathogens, especially bacterial pathogens. For instance, seed endophyte S. melonis can control crop diseases by producing anthranilic acid, which interferes with the sigma factor RpoS of the seed-borne pathogen Burkholderia plantarii [61]. Similarly, plant defense-related genes can also be induced by Sphingomonas sp., which is beneficial for plants against pathogens [62].

Conclusions

In conclusion, this study reveals that root and leaf-associated microbiota differentially respond to continuous monocultures. Microbiota analysis revealed that rhizosphere and leaf epiphytic microbiota were different, irrespective of cropping conditions, indicating the filtering effect of plant organs on the microbiota. Monocropping reduced the rhizosphere microbial population and diversity, while increased the leaf epiphytic microbial population and did not influence leaf epiphytic microbial diversity. In vitro and in vivo experiments, combined with correlation analyses, showed that monocropping weakened the antagonistic activity of rhizosphere microbiota against F. oxysporum and root rot disease, but enhanced the capacity of leaf epiphytic microbiota for A. alstroemeriae growth inhibition and leaf spot disease control. Overall, our results advance the understanding of the role of root and leaf-associated microbiota in response to cropping practices.

Availability of data and materials

No datasets were generated or analysed during the current study.

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Acknowledgements

We thank Xue Luo (Nanjing Normal University) for assisting in managing the field. We also thank Majorbio Cloud Platform (Shanghai, China) for assisting in bioinformatics analysis.

Funding

National Natural Science Foundation of China, 31870478, 32101277, Priority Academic Program Development (PAPD) of the Jiangsu Higher Education Institutions of China, China Postdoctoral Science Foundation, 2020M681657

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Authors and Affiliations

  1. Jiangsu Key Laboratory for Pathogens and Ecosystems, Jiangsu Engineering and Technology Research Center for Industrialization of Microbial Resources, College of Life Sciences, Nanjing Normal University, Nanjing, Jiangsu Province, China

    Hao-Ran Li, Xiang-Yu Zhang, Xin Xu, Yaseen Ullah, Chuan-Chao Dai & Wei Zhang

  2. Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, Jiangsu Province, China

    Kai-Ling He, Xin-Wen Chen & Ting-Ting Zhang

  3. State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Science, Nanjing, China

    Yan Chen

  4. Jiangsu Key Laboratory for Microbes and Functional Genomics, Jiangsu Engineering and Technology Research Center for Industrialization of Microbial Resources, College of Life Sciences, Nanjing Normal University, Nanjing, Jiangsu Province, China

    Wei Zhang

Authors
  1. Hao-Ran Li
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  2. Xiang-Yu Zhang
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Contributions

WZ contributed to the study’s conception and design. HRL, XYZ, KLH, XX, XWC, and YU conducted experiments and collected data. WZ and TTZ analyzed and interpreted the microbiota data. YC, CCD, and ZW revised the manuscript. WZ and TTZ wrote the draft manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Ting-Ting Zhang or Wei Zhang.

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Li, HR., Zhang, XY., He, KL. et al. Differential responses of root and leaf-associated microbiota to continuous monocultures. Environmental Microbiome 20, 13 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s40793-025-00675-9

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  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s40793-025-00675-9

Environmental Microbiome

ISSN: 2524-6372