Your new experience awaits. Try the new design now and help us make it even better

ORIGINAL RESEARCH article

Front. Microbiol., 04 February 2026

Sec. Microbiotechnology

Volume 17 - 2026 | https://doi.org/10.3389/fmicb.2026.1722838

Mechanism of Pantoea ananatis in the biocontrol of rice bacterial leaf blight

Ye Tian,,Ye Tian1,2,3Wenting Lei,,Wenting Lei1,2,3Jiayi Zhang,,Jiayi Zhang1,2,3Ying ShenYing Shen4Jianfei Lu
Jianfei Lu4*Munazza Ijaz,,Munazza Ijaz1,2,3Alhassan AlrafaieAlhassan Alrafaie5Temoor Ahmed,Temoor Ahmed6,7Chengqi Yan
Chengqi Yan8*Bin Li,,
Bin Li1,2,3*
  • 1State Key Laboratory of Rice Biology and Breeding, Ministry of Agriculture and Rural Affairs Key Laboratory of Molecular Biology of Crop Pathogens and Insect Pests, Hangzhou, China
  • 2Zhejiang Key Laboratory of Biology and Ecological Regulation of Crop Pathogens and Insects, Hangzhou, China
  • 3Zhejiang Engineering Research Center for Biological Control of Crop Pathogens and Insect Pests, Zhejiang Provincial Key Laboratory of Agricultural Microbiomics, Institute of Biotechnology, Zhejiang University, Hangzhou, China
  • 4Station for the Plant Protection and Quarantine and Control of Agrochemicals of Zhejiang Province, Hangzhou, China
  • 5Department of Medical Laboratory, College of Applied Medical Sciences in Al-Kharj, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
  • 6Xianghu Laboratory, Hangzhou, China
  • 7Department of Plant Biotechnology, Korea University, Seoul, South Korea
  • 8Modern Agriculture College, Zhejiang Wanli University, Ningbo, China

Introduction: Rice bacterial leaf blight, caused by Xanthomonas oryzae pv. oryzae (Xoo), is a highly destructive disease. Within the rice-Xoo pathosystem, Pantoea ananatis exhibits a dual role, functioning both as a pathogen and as a biocontrol agent, underscoring the need to clarify its speciffc functions for effective disease management.

Methods: Isolated strains ZJU1-ZJU18 were identified using multi-locus sequence analysis, core-genome phylogenomic analysis, and average nucleotide identity. The population density of Xoo in rice leaves was determined by plate counting and qPCR to evaluate the inhibitory effect of P. ananatis on its growth.

Results and discussion: The isolated strains ZJU1-ZJU18 were all identiffed as P. ananatis, and they exhibited plant growth-promoting traits, including phosphate solubilization, siderophore production, and indole-3-acetic acid synthesis. Furthermore, strains ZJU1-ZJU18 did not induce rice bacterial leaf blight symptoms under the experimental conditions, with the lesion inhibition rate against this disease ranging from 95.14 to 97.92%. Mechanistic investigations revealed that P. ananatis suppressed Xoo via nutrient competition, dominating co-culture systems (>90% relative abundance) and reducing Xoo colonization on rice leaves by 96.78–99.00%. Xoo infection enhanced P. ananatis colonization, likely by modifying the leaf microenvironment. Furthermore, the results of species composition analysis showed that P. ananatis could alter the structure and diversity of the microbial community in rice leaves and reduce the abundance of Xanthomonas species. The principal coordinate analysis indicated that P. ananatis had a more signiffcant impact on the microbial community composition than Xoo. This study found that P. ananatis may inhibit the pathogen Xoo through nutrient competition and reshape the microbial structure at the community level.

1 Introduction

The bacterium Xanthomonas oryzae pv. oryzae (Xoo) has become a pervasive threat to rice production across diverse agroecological zones globally (Ramprasad et al., 2024). The occurrence and severity of the disease are influenced by rice cultivar., growth stage, geographic location, and environmental conditions (Duku et al., 2016; Chumpol et al., 2022; Sumuni et al., 2024). The pathogen Xoo enters through wounds or hydathodes, spreads systemically via xylem vessels, colonizes the mesophyll tissues of rice, and predominantly infects leaves and leaf sheaths (Timilsina et al., 2020; Cao et al., 2021). Due to the spread of Xoo through straw, seeds, and water, disease outbreaks are most severe under high humidity, heavy rainfall, and typhoon weather conditions (Gnanamanickam et al., 1999; Ritbamrung et al., 2025).

Although some new methods have been reported to control plant diseases (Ahmed et al., 2023; Noman et al., 2023), biological control represents an environmentally sustainable alternative to chemical control, offering advantages such as ecological safety, adaptability, minimal impact on non-target organisms, food safety, and sustained efficacy over time (Liu et al., 2023; Zhang et al., 2024; He et al., 2025). In the management of rice bacterial leaf blight, biocontrol bacteria have demonstrated promising effects. These bacteria not only suppress Xoo growth through the secretion of antibacterial metabolites but also diminish its competitive advantage through mechanisms such as eliciting rice immune responses and competing for nutrients and ecological niches (Ooi et al., 2022; Islam et al., 2023).

Pantoea can be isolated from animals, humans, plants, water, and soil, and exists in ecological roles as pathogens, symbiotic bacteria, endophytic bacteria, and saprophytic bacteria, demonstrating a high degree of ecological diversity (Walterson and Stavrinides, 2015; Lv et al., 2022). Pantoea shows high genetic similarity among its members (Azizi et al., 2020; Kini et al., 2021). To date, the genus has been classified into over 25 species that share phenotypic similarities, among which P. ananatis, P. agglomerans, P. dispersa, P. vagans, and P. stewartii have been the most extensively studied (Toh et al., 2019; Arayaskul et al., 2020; Dahiya et al., 2024; Tian et al., 2024).

In plant ecosystems, Pantoea species exhibit both beneficial and detrimental effects. Certain Pantoea strains can promote crop growth and enhance plant health through mechanisms such as nutrient provision, phytohormone synthesis, suppression of plant pathogens, induction of broad-spectrum plant resistance, and alleviation of abiotic stresses, including heavy metal pollution (Sun et al., 2022; Krishnappa et al., 2024). Conversely, some Pantoea strains can cause the plant leaf spot disease, leaf blight disease, and soft rot disease, leading to significant economic losses (Xue et al., 2021; Yu et al., 2022; Luna et al., 2023; Wang et al., 2025).

P. ananatis exhibits a complex dualistic role in rice disease systems. Duan et al. (2025) has identified P. ananatis JMS78-1 as a potential pathogen responsible for rice bacterial leaf blight. However, Jiang et al. (2025) has reported P. ananatis YN26 can be used as a biological control agent to control rice bacterial leaf blight. The role of P. ananatis in rice production has attracted considerable interest and has become a hot topic of current research.

In this study, P. ananatis strains ZJU1-ZJU18 were isolated from rice leaves affected by bacterial leaf blight. Through in vitro and in vivo experiments, we investigated the pathogenicity of strains ZJU1-ZJU18 and their inhibitory effects on Xoo. Using strain ZJU2 as a model, molecular biology techniques and microbiome analysis were employed to elucidate the mechanism by which P. ananatis modulates rice bacterial leaf blight. This study aims to clarify the relationship between P. ananatis and disease development, and provide novel strategies for disease management.

2 Materials and methods

2.1 Bacterial strains, plasmid and reagents

In this study, P. ananatis strains ZJU1-ZJU18 were isolated from rice leaves affected by rice bacterial leaf blight, collected from field sites in Wenzhou, Hangzhou, Quzhou, Shaoxing, Ningbo, Taizhou, Jinhua, Suqian, Huai’an, Chizhou, Guiping, and Jiangmen cities. The Xoo strains C2, PXO99A, and N1, along with the plasmids pBBR1MCS-5, pBBR1MCS-RFP, and pRADK-GFP, were obtained from the Plant Bacteriology Laboratory at Zhejiang University. The plasmid pBBR1MCS2-luxCDABE was generously provided by the Plant-Microbe Interaction Laboratory at Zhejiang University.

Bacterial isolation was performed using tryptic soy agar (TSA) medium. Xoo and P. ananatis were grown in nutrient broth (NB) medium at 30 °C. The composition of media used in this study are described below. TSA medium was prepared with 15 g tryptone, 5 g soybean peptone, 5 g NaCl and 15 g agar per liter of distilled water. The pH was adjusted to 7.0 prior to autoclaving at 121 °C for 15 min. NB medium was prepared with 10 g tryptone, 3 g beef extract, and 5 g NaCl per liter of distilled water. The pH was adjusted to 7.0 prior to autoclaving at 121 °C for 15 min. Methyl Red-Voges Proskauer (MR-VP) medium was prepared with 5 g peptone, 5 g glucose, and 3.8 g K2HPO4 per liter of distilled water. The pH was adjusted to 7.0, and the medium was sterilized by autoclaving at 121 °C for 15 min. Nitrogen-limited (NL) medium was prepared with 10 g glucose, 1 g KH2PO4, 1 g K2HPO4, 0.2 g MgSO4·7H2O, 0.5 g NaCl, 0.1 g CaSO4, 0.05 g FeSO4, and 0.05 g MnSO4 per liter of distilled water. The pH was adjusted to 7.0, and the medium was sterilized by autoclaving at 121 °C for 15 min. Carbon-limited (CL) medium was prepared with 1 g KH2PO4, 1 g K2HPO4, 0.5 g NH4Cl, 0.2 g MgSO4·7H2O, 0.5 g NaCl, 0.1 g CaSO4, 0.05 g FeSO4, and 0.05 g MnSO4 per liter of distilled water. The pH was adjusted to 7.0, and the medium was sterilized by autoclaving at 121 °C for 15 min. Chrome azurol S (CAS) medium was prepared by combining, per liter, 100 mL of 10 × PIPES buffer, 20 g glucose, 10 g peptone, 0.5 g MgSO4·7H2O, and 0.5 g of CaCl2. Following sterilization by autoclaving (121 °C, 15 min) and cooling, 100 mL of sterile, pre-mixed CAS detection solution (containing Chrome Azurol S, FeCl3·6H2O, and hexadecyltrimethylammonium bromide) was added aseptically.

Protease, cellulase, amylase, Mongina organic/inorganic phosphorus media, CAS medium, oxidase test strips, methyl red (MR) reagent, voges proskauer (VP) reagent, hydrogen peroxide, and Lugol’s iodine solution-were purchased from Hopebio biotechnology Co., Ltd. Both media were prepared in sterile distilled water and adjusted to pH 7.0 at 25 °C. Bacterial DNA from rice leaves was extracted using the QIAGEN PowerSoil Kit. Quantitative PCR (qPCR) assay was performed using HisenBio SYBR Green Master Mix. Besides, kanamycin (Km) and gentamicin (Gen) sulfate were applied at a concentration of 50 μg/mL.

2.2 Isolation and identification of Pantoea ananatis

2.2.1 Isolation of Pantoea ananatis

Pantoea strains were isolated following a modified protocol adapted from Yang et al. (2020). Rice leaves were surface-sterilized by wiping with 75% ethanol-soaked cotton, followed by immersion in 1.2% (v/v) sodium hypochlorite solution for 5 min and rinsing 3 times with sterile water. The absence of bacterial growth in the final rinse water confirmed effective surface sterilization. The sterilized leaves were homogenized in 1 mL of sterile water containing sterile steel beads using a leaf tissue grinder for 1 min. After brief centrifugation, 100 μL of the supernatant was collected, serially diluted, and spread evenly onto TSA plates. The plates were incubated at 30 °C for 10 d. Individual colonies were picked and purified via repeated streaking on TSA to obtain pure cultures. Isolated single colonies were amplified using 16S-F/R primers, and the resulting PCR products were sequenced bidirectionally. Based on the sequencing results analyzed through the NCBI database, colonies identified as belonging to the genus Pantoea were selected for subsequent research.

2.2.2 Construction of 16S rRNA phylogenetic tree

The method for constructing the 16S rRNA phylogenetic tree was modified based on Tambong (2019). First, the 16S rRNA genes were amplified from the isolated Pantoea strains, and the resulting PCR products were subjected to bidirectional sequencing. Subsequently, the corresponding 16S rRNA gene sequences of related Pantoea strains were retrieved from the NCBI database and aligned using Clustal W (v2.1) for multiple sequence alignment. Finally, based on the aligned sequences, a phylogenetic tree was constructed using the neighbor-joining (NJ) method in MEGA11 software.

2.2.3 Construction of multi-locus sequence analysis phylogenetic tree

Multi-locus sequence analysis (MLSA) can overcome the limitations of 16S rRNA gene sequencing in species-level resolution and providing a reliable taxonomic foundation for subsequent research (Komaki, 2022). The method for constructing the MLSA phylogenetic tree was modified based on Tambong (2019). First, the conserved genes atpD, fusA, gyrB, and rpoB were amplified from Pantoea strains identified by 16S rRNA analysis, using gene-specific primers (Supplementary Table S1). Pantoea strains using amplification primers, and the resulting PCR products were subjected to bidirectional sequencing using sequencing primers. The primers used in this study are listed in Table 1. The NCBI accession numbers of the atpD, fusA, gyrB, and rpoB genes for strains ZJU1-ZJU18 are provided in Supplementary Table S2.

Table 1
www.frontiersin.org

Table 1. Population sizes of Xoo and P. ananatis after co-culture in different broth.

For a robust phylogenetic analysis, a comprehensive set of reference sequences was obtained from the NCBI database. The selection included type strains and additional representative strains across Pantoea species, with an emphasis on groups phylogenetically close to the isolates of this study. The sequencing reads for each gene were separately assembled and verified using SeqMan Pro (DNASTAR v15) to obtain a single consensus sequence for each strain. Subsequently, multiple sequence alignments for each gene set were independently performed using Clustal W (v2.1). After manual inspection of all gene alignments, they were concatenated head-to-tail in the order of atpD-gyrB-rpoB-fusA to generate an overall supermatrix for phylogenetic analysis. The concatenated alignment was manually trimmed in MEGA11 to remove non-aligned regions at both ends of all sequences and to delete any alignment columns containing gaps in more than 50% of the sequences, ensuring higher homology of the sites used for tree inference. Finally, phylogenetic trees were constructed in MEGA11 using the NJ and maximum likelihood (ML) methods, respectively. Branch support for the trees were assessed with 1,000 bootstrap replicates.

2.2.4 Genome sequencing

A single colony of strain ZJU2 was inoculated into NB broth and incubated at 28 °C. When the culture reached an OD600 of 0.8, a 5 mL aliquot was centrifuged at 8,000 × g for 5 min to pellet the cells. The bacterial pellet was washed twice with sterile phosphate-buffered saline (PBS) and collected by centrifugation. The final pellet was sent to Novogene bioinformatics technology Co., Ltd. for whole-genome sequencing. The company performed sequencing using a combined strategy with the Illumina NovaSeq platform and the Oxford Nanopore PromethION platform. After quality control of the raw data, hybrid assembly and polishing were conducted using software such as Unicycler, ultimately yielding the complete circular genome sequence of strain ZJU2.

2.2.5 Average nucleotide identity

Average nucleotide identity (ANI) is a crucial criterion for bacterial species delineation, where strains with an ANI value of >95% are classified as conspecific (Goris et al., 2007). The complete genome sequences of strain ZJU2 and the reference strain P. ananatis LMG 2665T were submitted to the EzGenome online analysis platform1 for ANI calculation.

2.2.6 Construction of core-genome phylogenomic tree

Representative strains of other species within the genus Pantoea were retrieved from the National Center for Biotechnology Information (NCBI) database. The core-genome phylogenomic tree was constructed using EasyCGTree V4.2 (Zhang et al., 2023). Specifically, HMMER was employed for homologous gene retrieval, MUSCLE5 for sequence alignment, trimAl for conservative region screening, and FastTree/IQ-TREE for phylogenetic tree construction.

2.3 Property determination of Pantoea ananatis

According to the method described by Tariq et al. (2023), we evaluated the bacterial swimming, phosphate solubilization, siderophore production, and indole-3-acetic acid (IAA) production of P. ananatis strains ZJU1-ZJU18.

2.3.1 Swimming, methyl red, and voges proskauer tests

Pantoea ananatis strains ZJU1-ZJU18 were inoculated into MR-VP medium and cultured until the OD600 of the bacterial suspensions reached 0.8, corresponding to 2 × 108 CFU/mL. Firstly, we spotted 3 μL of bacterial suspension onto NB medium containing 0.3% agar and incubated at 30 °C for 1 d to observe bacterial swimming. Then, we added VP detection solution A and solution B to the bacterial solution. If the color of the solution changed from pink to red within 2 min, the VP detection result was positive. In addition, we added the MR indicator solution to the bacterial solution. If the solution immediately turned red, it indicated that the MR detection result was positive.

2.3.2 Enzyme activity determination

The 3% hydrogen peroxide solution was applied to the colonies of P. ananatis strains ZJU1-ZJU18. The appearance of bubbles indicated the presence of contact enzyme activity in the bacteria. The strains were cultured on amylase detection plates at 30 °C for 3 d, followed by the addition of a drop of Lugol’s iodine solution to the edge of the colonies. If no color change was observed, this suggested that the bacteria possess starch hydrolysis activity. P. ananatis strains ZJU1-ZJU18 were subsequently cultured on cellulase detection plates at 30 °C for 3 d. The formation of a transparent hydrolysis zones around the bacterial cells indicated cellulase production. Similarly, the strains were cultured on protease detection plates at 30 °C for 3 d, and the appearance of a transparent hydrolysis zones around the bacterial cells indicated protease production.

2.3.3 Phosphate solubilization and siderophore activity detection

P. ananatis strains ZJU1-ZJU18 were cultured on Mongina inorganic phosphate and Mongina organic phosphate solid media at 30 °C for 3 d to evaluate their ability to dissolve phosphate. The phosphate solubilization zones around the colonies was observed, and the diameters of these zones were measured. Furthermore, P. ananatis strains ZJU1-ZJU18 were cultured on CAS agar plates at 30 °C for 3 d to assess siderophore production. The presence of yellow halos surrounding the colonies was recorded, and their diameters were measured accordingly.

2.3.4 IAA synthesis detection

First, the IAA standard solutions with concentrations ranging from 0 to 100 μg/mL were mixed with equal volumes of Salkowski reagent and incubated in the dark for 30 min. The absorbance was measured at 530 nm, and a standard curve was generated using Microsoft Excel. Subsequently, strains ZJU1-ZJU18 were inoculated into LB broth supplemented with L-tryptophan (200 μg/mL) and incubated for 3 d. The cultures were centrifuged at 12,000 × g for 3 min to obtain the supernatant. A volume of 1,500 μL of the supernatant was mixed with an equal volume of Salkowski reagent. After standing in the dark for 30 min, the absorbance of the mixture was measured at 530 nm. Finally, the IAA concentration produced by each strain was calculated based on the standard curve.

2.4 Pathogenicity assay of Pantoea ananatis

2.4.1 Leaf inoculation assay

Rice seeds were sterilized, germinated, and then three germinated seeds were transplanted into each pot (13 cm in diameter) filled with sterilized soil. The plants were cultivated in a greenhouse maintained at 28 °C with 70% relative humidity and a 16 h photoperiod. After 4 weeks of growth, the plants were used for inoculation. The bacterial suspensions (OD600 = 0.8) of P. ananatis strains ZJU1-ZJU18 were inoculated into rice leaves using the clip inoculation method (Luna et al., 2023). Sterile water was used as a negative control, and the bacterial suspension (OD600 = 0.8) of Xoo strain C2 was served as a positive control. Leaf disease symptoms were evaluated at 14 days post-inoculation (dpi). The experiments were performed with 3 replicates.

2.4.2 Seed inoculation assay

The sterilized rice seeds were fully immersed in a suspension of P. ananatis (OD600 = 0.8) prepared in PBS and soaked at 28 °C for 2 h, with PBS used as a negative control. After soaking, the seeds were removed and gently blotted on sterile filter paper to remove excess liquid. They were then evenly placed on moist, sterile filter paper in Petri dishes, with 20 seeds per dish. The dishes were transferred to a growth chamber set at 28 °C under a 12 h light/12 h dark cycle for germination and growth. Germination symptoms were assessed after 3 d of cultivation.

2.5 Antibacterial activity of Pantoea ananatis against Xoo in vivo

Rice plants were cultivated as described in Section 2.4.1. After 4 weeks of growth, the plants were subjected to inoculation treatment. A mixture of sterile water and Xoo suspension served as the positive control, while sterile water alone was used as the negative control. In each independent experiment, at least ten rice leaves were treated for each treatment group. Lesion lengths on the leaves were measured at 14 dpi, and the experiments were independently repeated 3 times. In each independent experiment, at least ten rice leaves were treated for each treatment group. The disease control efficacy was calculated using the formula: Disease control efficacy = [(Lesion length of positive control – Lesion length of treatment) / Lesion length of positive control] × 100%.

2.5.1 Antibacterial activity of multiple Pantoea ananatis strains

Resuspend the cell pellet of P. ananatis strains ZJU1-ZJU18 and Xoo strain C2 in sterile water and adjust the concentration to an OD600 value of 0.8. Equal volumes of the resuspended P. ananatis and Xoo suspensions were mixed. The mixed suspensions, positive control, and negative control were inoculated onto the leaves of Nipponbare rice using the leaf-clipping method.

2.5.2 Effect of inoculation ratio on antibacterial activity

Resuspend the cell pellet of P. ananatis strains ZJU2 and Xoo strain C2 in sterile water and adjust the concentration to an OD600 value of 0.8. Xoo suspensions and P. ananatis suspensions were mixed at ratios of 1: 1, 10: 1, and 100: 1. The mixed suspensions, positive control, and negative control were inoculated onto the leaves of Nipponbare rice using the leaf-clipping method.

2.5.3 Activity of strain ZJU2 against different Xoo strains

Resuspend the cell pellet of P. ananatis strains ZJU2 and Xoo strain C2, PXO99A and N1 in sterile water and adjust the concentration to an OD600 value of 0.8. Equal volumes of the resuspended P. ananatis and Xoo suspensions were mixed. The mixed suspensions, positive control, and negative control were inoculated onto the leaves of Nipponbare rice using the leaf-clipping method.

2.5.4 Activity comparison between rice varieties

Resuspend the cell pellet of P. ananatis strains ZJU2 and Xoo strain C2 in sterile water and adjust the concentration to an OD600 value of 0.8. Equal volumes of the resuspended P. ananatis and Xoo suspensions were mixed. The mixed suspensions, positive control, and negative control were separately inoculated onto the leaves of Nipponbare rice and 9,311 rice using the leaf-clipping method.

2.6 Antibacterial activity of Pantoea ananatis against Xoo in vitro

The antibacterial activity of P. ananatis was evaluated with minor modifications with minor modifications to the method described by Xie et al. (2023). First, 1 mL of Xoo strain C2 suspension (OD600 = 0.8) was mixed with 7 mL of semi-solid NA medium (0.8% agar) to prepare the double-layer Xoo plate. Subsequently, 3 μL of P. ananatis suspension (OD600 = 0.8) was spotted onto the double-layer Xoo plate. After the suspension was absorbed, the plates were incubated at 30 °C for 48 h, and the formation of inhibition zones was observed and recorded.

To assess the antibacterial activity of P. ananatis cell-free fermentation broth against Xoo, strains ZJU1-ZJU18 were inoculated into 100 mL of NB broth and incubated with shaking at 30 °C for 72 h. The culture was centrifuged at 12,000 × g for 10 min, and the supernatant was filtered through a 0.22 μm sterile membrane to obtain the cell-free fermentation broth. A hole (8 mm in diameter) was punched in the center of the Xoo double-layer plate, and 100 μL of the cell-free fermentation broth was added to each hole. The plates were incubated at 30 °C for 48 h, and the formation of inhibition zones was observed.

2.7 Bacterial growth curve assay

The concentrations of Xoo strain C2 and P. ananatis strain ZJU2 suspensions were adjusted to 1.0 × 108 CFU/mL. Add 100 μL Xoo and P. ananatis to 5 mL NB broth, respectively. Subsequently, the culture was incubated at 30 °C for 48 h. The OD600 was measured at 3 h intervals, and the growth curves were generated accordingly. The specific growth rate (μ) was calculated based on the growth curve. Data points with optical density (OD600) values between 0.1 and 0.6 were selected, as within this range the OD value exhibits a linear relationship with cell concentration. The natural logarithm was taken of these OD values to obtain ln(OD). Using cultivation time as the independent variable and ln(OD) as the dependent variable, linear regression analysis was performed on the data points corresponding to the exponential growth phase. The resulting linear equation is y = ax + b, where the slope a represents the specific growth rate μ (h−1).

2.8 Flow cytometry analysis

To construct the fluorescent strain Pa (GFP), the plasmid pRADK-GFP was introduced into P. ananatis strain ZJU2. The concentrations of Xoo strain C2 and P. ananatis strain Pa (GFP) suspensions were adjusted to 1.0 × 108 CFU/mL. Subsequently, the two strains were co-inoculated into 5 mL of NB medium at initial volume ratios of 1: 1, 10: 1, and 100: 1. For the monoculture control, an equivalent volume of Pa (GFP) suspension was inoculated into 5 mL of NB broth, with sterile NB broth added in place of the Xoo suspension. After incubation at 30 °C with shaking for 72 h, the proportion of GFP-positive cells in each suspension was determined by flow cytometry. The relative abundance of P. ananatis in the co-culture system was calculated as follows: Relative abundance of P. ananatis = [(Proportion of GFP-positive cells in co-culture)/(Proportion of GFP-positive cells in monoculture)] × 100%.

2.9 Bacterial count of culture medium

To differentiate between P. ananatis and Xoo in co-culture broth, we introduced plasmid pBBR1MCS RFP carrying Km resistance gene into Xoo strain C2 to construct marker strain Xoo (RFP), and vector pBBR1MCS-5 carrying Gen resistance gene into P. ananatis strain ZJU2 to construct marker strain Pa (Gen). The population densities of Xoo and P. ananatis in co-culture broth could be independently quantified by counting colony-forming units on selective media amended with either Km or Gen.

The bacterial suspensions of Xoo (RFP) and Pa (Gen) were adjusted to a concentration of 1.0 × 108 CFU/mL. Subsequently, Xoo (RFP) and Pa (Gen) were co-inoculated into NB broth, NL broth, and CL broth at initial volume ratios of 1: 1, 10: 1, and 100: 1. The cultures were incubated at 30 °C for 3 d, after which the mixed bacterial suspensions were subjected to 10-fold serial dilutions. Aliquots of 2.5 μL from each dilution were spotted onto NB, NL, and CL agar plates supplemented with either Km or Gen. The plates were incubated at 30 °C for 3 d, and the number of colonies was counted.

2.10 Spot assay

The bacterial suspensions of Xoo (RFP) and Pa (Lux) were adjusted to a concentration of 1.0 × 108 CFU/mL. On the bottom of a NA plate containing Km, a inverted “V” shape was drawn with a marker to guide inoculation. Then, 2.5 μL of Pa (Lux) and Xoo (RFP) suspensions were inoculated separately along the guide lines on the NA plate. The plate was incubated upright at 28 °C for 48 h, after which the growth of P. ananatis and Xoo colonies was observed.

2.11 Bacterial count of rice leaves

The cultivation of Nipponbare rice plants followed the method described in Section 2.4.1. Prior to inoculation, the bacterial suspensions of Xoo (RFP) and Pa (Gen) were adjusted to a concentration of 1.0 × 108 CFU/mL. Rice leaves were inoculated with Xoo (RFP) alone, Pa (Gen) alone, or a mixture of both using the leaf-clipping method. Samples were subsequently collected at 1, 3, 7, and 14 dpi. After the surface sterilization of rice leaves, the absence of bacterial growth in the final rinse water confirmed the effectiveness of the sterilization process.

For qPCR analysis, six leaves were collected per treatment at each time point. Following surface sterilization, total genomic DNA was extracted from the tissues using the QIAGEN PowerSoil DNA Extraction Kit. The bacterial populations were quantified by qPCR with species-specific primers, and absolute counts were calculated based on a standard curve.

For the drop plate assay, three leaves were collected per treatment at each time point. After the same surface sterilization procedure, leaves were homogenized. The resulting leaf homogenates were serially diluted tenfold, and 2 μL aliquots of each dilution were spotted onto NA plates supplemented with the appropriate antibiotics. After incubation at 30 °C for 72 h, the number of colony-forming units was counted to determine the viable bacterial population.

2.12 Leaf bioluminescence imaging assay

The leaf bioluminescence imaging assay was conducted with slight modifications to the previously described method by Xu et al. (2022). The pBBR1MCS2-luxCDABE plasmid was successfully introduced into P. ananatis strain ZJU2 to generate the luminescent strain Pa (Lux). Subsequently, Xoo strain C2 and P. ananatis strain Pa (Lux) were adjusted to a concentration of 1.0 × 108 CFU/mL.

Nipponbare rice leaves were inoculated with a mixed suspension of P. ananatis and Xoo using the leaf-clipping method. For the control treatment, leaves were inoculated with a suspension of P. ananatis mixed with an equivalent volume of NB broth. At 1, 3, 7, and 14 dpi, the rice leaves were collected. After the surface sterilization of rice leaves, the absence of bacterial growth in the final rinse water confirmed the effectiveness of the sterilization process. The bioluminescent signals were monitored using a single-photon imaging system equipped with a Photek HRPCS5 camera (Photek Ltd., East Sussex, United Kingdom) with an acquisition time of 5 min. Finally, the quantitative data were exported using Image32 software (version 3.6.2) for analysis.

2.13 16S amplicon sequencing of the phyllosphere endophytic microbiome

Nipponbare rice leaves were collected at 1 and 14 dpi under four treatment conditions: uninoculated control, inoculated with Xoo, inoculated with P. ananatis, and co-inoculated with both Xoo and P. ananatis. Leaf samples were flash-frozen in liquid nitrogen, and 0.2 g of each sample was ground into a fine powder using a leaf tissue grinder. Samples from different treatment groups should be randomly mixed as much as possible for library construction and sequencing, so as to reduce potential batch effects. Total genomic DNA was extracted using the QIAGEN PowerSoil DNA Isolation Kit. Subsequently, the V4-V5 hypervariable region of the bacterial 16S rRNA gene was amplified using region-specific primers. The resulting amplicons were purified, quantified, and subjected to paired-end sequencing by Parsono Biotechnology Co., Ltd. (Shanghai, China). Raw sequence data were processed using the DADA2 pipeline, which included primer trimming, quality filtering, denoising, merging of paired reads, and removal of chimeric sequences. After quality control, unique sequences were identified as amplicon sequence variants (ASVs). A feature table was generated based on the abundance of ASVs across samples. For alpha/beta diversity analysis, all samples were uniformly rarefied to 95% of the sequence number of the sample with the lowest sequencing depth. Downstream data analyses were conducted using the GenesCloud online platform.2

3 Results

3.1 Identification of Pantoea ananatis

Multiple Pantoea isolates were obtained from each sampling site. The 16S rRNA gene sequences of all isolates were aligned and compared, and isolates exhibiting identical or nearly identical sequences (>99.5% similarity) were grouped into the same operational taxonomic unit (OTU). From each OTU at each sampling site, one isolate was selected as a representative strain for subsequent molecular phylogenetic and functional analyses. These isolates were designated ZJU1 through ZJU18, and their corresponding sequencing data were deposited into the NCBI database (Supplementary Table S3). The phylogenetic tree based on 16S rRNA gene sequence analysis revealed that the isolated Pantoea strains belonged to P. ananatis (Figure 1).

Figure 1
Phylogenetic tree diagram showing the evolutionary relationships among various Pantoea species and strains. Highlighted in green are closely related strains labeled ZJU2 through ZJU18 and Pantoea ananatis CU: ASL: TSB2. The tree includes bootstrap values at branch points, with a scale bar indicating evolutionary distance.

Figure 1. Phylogenetic tree based on 16S rRNA gene sequence analysis. Numbers at the nodes represent bootstrap support values estimated from 1,000 replicates. Only values above 50% are displayed.

MLSA can infer phylogenetic relationships by integrating sequence information from multiple conserved genes, thereby improving resolution and accuracy (Brady et al., 2008; Tambong, 2019; Suleimanova et al., 2021; Guedj-Dana et al., 2022). Following the recommended criteria for species demarcation outlined in the study by De Armas et al. (2022), we found that the core clustering patterns of the two MLSA phylogenetic trees constructed using the NJ and ML methods were highly congruent. Strains ZJU1-ZJU18 formed a major clade with members of the P. ananatis group (Figure 2). The relationships among other species (P. allii, P. stewartii, P. vagans, P. agglomerans, etc.) were also largely consistent between the two methods. In the MLSA phylogeny based on the NJ method, the major clade comprising strains ZJU1-ZJU18 and the P. ananatis group received a bootstrap support value of 100. Within this clade, ZJU17 clustered with P. ananatis strain JT8-6 with a support value of 90, while ZJU14 clustered with P. ananatis strain TZ39 with a support value of 65 (Figure 2A). Therefore, we concluded that strains ZJU1-ZJU18 are all P. ananatis.

Figure 2
Phylogenetic trees labeled A and B. Both trees display branch structures showing evolutionary relationships among various Pantoea strains. Tree A is highlighted in pink, and Tree B in blue, with red text denoting certain strains labeled ZJU1 to ZJU18. Branch numbers indicate the branch support values. Both trees identify closely related strains of Pantoea ananatis and its various isolates, with additional species below. Scale bars represent genetic distance.

Figure 2. MLSA phylogenetic trees constructed based on the conserved genes atpD, gyrB, fusA, and rpoB. (A) Neighbor-joining method. (B) Maximum likelihood method. Numbers at the nodes represent bootstrap support values estimated from 1,000 replicates. Only values above 50% are displayed.

Whole-genome sequencing of the representative strain ZJU2 revealed a genome comprising one chromosome and one plasmid. The chromosome is 4,472,381 bp in length with a G + C content of 53.59%, while the plasmid is 365,824 bp with a G + C content of 52.37%. The complete genome sequence has been deposited in the NCBI database under accession number SUB15922611. A circular map of the chromosome is presented in Supplementary Figure S1, displaying from outermost to innermost: genomic coordinates, protein-coding genes, functional annotations, ncRNAs, genomic GC content, and GC skew.

To taxonomically classify ZJU2, we performed ANI analysis against P. ananatis strain LMG 2665T. The resulting ANI value was 99.28%, substantially above the 95.00% threshold widely used for species delineation (Goris et al., 2007). Therefore, based on genomic evidence, strain ZJU2 was identified as P. ananatis.

Based on core-genome phylogenomic analysis, we clarified the taxonomic status of strain ZJU2 and its evolutionary relationships within the species P. ananatis (Figure 3). The tree revealed a well-resolved phylogeny with strong support at key nodes. Critically, all P. ananatis strains, including ZJU2, formed a monophyletic clade with maximum (100%) bootstrap support, providing robust genomic evidence that ZJU2 belongs to this species. Within the P. ananatis clade, strain ZJU2 clustered most closely with the reference strain LMG 20103. At the genus level, P. ananatis was clearly distinguished from other species such as P. stewartii and P. dispersa, each forming independent, well-supported evolutionary branches, further validating the reliability of the core-genome phylogenomic analysis performed here.

Figure 3
Circular phylogenetic tree displaying various strains of the Pantoea genus, indicated by distinct color segments. Each segment corresponds to a species or subspecies listed in the legend on the right, using shades from purple to green. The tree scale is 0.009.

Figure 3. Core-genome phylogenomic tree of the genus Pantoea. Distinctly colored clades correspond to discrete species of the genus Pantoea, as delineated in the legend. The tree scale (0.009) denotes the genetic distance. Values adjacent to nodes represent bootstrap support (derived from 1,000 replicates), and only those exceeding 50 are depicted in the figure.

3.2 Characterization of Pantoea ananatis traits

This study found that the VP test produced positive results for P. ananatis strains ZJU1-ZJU18, while the MR test was negative. Enzyme activity assays revealed that strains ZJU1-ZJU18 did not produce catalase, cellulase, protease, or amylase. Furthermore, all strains ZJU1-ZJU18 exhibited good swimming (Supplementary Figure S2A). Besides, strain ZJU18 displayed the strongest swimming ability, with a swimming diameter of 63.67 mm, whereas strain ZJU10 showed the weakest swimming ability, with a swimming diameter of 15.33 mm (Supplementary Table S4). Bacteria possessing plant growth-promoting (PGP) traits can promote plant growth. Our research found that P. ananatis strains ZJU1-ZJU18 could form clear halos on both inorganic and organic phosphate plates, demonstrating their ability to dissolve both inorganic and organic phosphates (Supplementary Figures S2B,C). Quantitative analysis indicated that strain ZJU4 exhibited the highest inorganic phosphate solubilization capacity, with a halo diameter of 3.23 mm, while strain ZJU14 showed the strongest organic phosphate solubilization, with a halo diameter of 22.33 mm (Figures 4A,B). Except for strain ZJU11, other isolated P. ananatis strains formed characteristic yellow halos on CAS plates (Supplementary Figure S2D), indicating siderophore production. Strain ZJU2 displayed the strongest siderophore synthesis capacity, with a halo diameter of 44.53 mm (Figure 4C). Besides, the standard curve for IAA quantification was established using spectrophotometry, yielding the equation: y = 0.01x + 0.1089 (R2 = 0.9794). Our study demonstrated that all P. ananatis strains were capable of synthesizing IAA. Notably, strains ZJU12, ZJU11, ZJU17, and ZJU14 exhibited significantly higher IAA production levels, with yields of 172.78 μg/mL, 169.30 μg/mL, 166.98 μg/mL, and 164.97 μg/mL, respectively (Figure 4D).

Figure 4
Four bar charts labeled A, B, C, and D, depict different measurements for various strains: A and B show solubilization zone diameters in millimeters, with A ranging from 1 to 3 mm and B from 8 to 24 mm. C displays the diameter of yellow holes in millimeters, ranging from 10 to 50 mm. D illustrates IAA production in milligrams per liter, ranging from 50 to 150 mg/L. Each strain is represented by a distinct colored bar with annotations for statistical significance.

Figure 4. Determination of the promoting properties of ZJU1–ZJU18. (A) Inorganic phosphorus solubilization. (B) Organic phosphorus solubilization. (C) Siderophore production. (D) IAA production. Statistical differences were analyzed by one-way ANOVA. Different lowercase letters within the same time point and assay indicate significant differences between treatments (p < 0.05).

3.3 Pantoea ananatis can suppress rice bacterial leaf blight in greenhouse

Leaf-clipping assays showed that rice leaves inoculated with sterile water exhibited no significant lesions. In contrast, leaves inoculated with Xoo strain C2 developed characteristic yellowish-brown lesions that expanded along the leaf veins. However, Rice leaves inoculated with P. ananatis strains ZJU1-ZJU18 exhibited no significant disease symptoms, with only minor chlorotic spots observed at the inoculation sites. Based on these results, we concluded that P. ananatis strains ZJU1-ZJU18 did not induce leaf blight symptoms under the tested conditions (Figure 5A). Furthermore, we observed that these strains did not inhibit the germination of rice seeds (Supplementary Figure S3; Supplementary Table S5).

Figure 5
Two panels labeled A and B display rows of eighteen green leaves each, marked with identifiers ZJU1 to ZJU18. In panel A, the leaves exhibit various degrees of yellowing and discoloration, particularly near the margins. In panel B, leaves appear generally less affected, maintaining a more uniform green color. Controls labeled H₂O and Xoo are also shown.

Figure 5. Rice leaf symptoms observed at 14 dpi with different bacteria. (A) Inoculation with P. ananatis strains ZJU1–ZJU18. (B) Co-inoculation with P. ananatis strains ZJU1–ZJU18 and Xoo strain C2.

To investigate whether different P. ananatis strains consistently exhibit inhibitory effects on the development of rice bacterial leaf blight, we co-inoculated P. ananatis strains ZJU1-ZJU18 individually with Xoo strain C2 onto the leaves of japonica rice cultivar Nipponbare. The results revealed that rice leaves inoculated with Xoo and sterile water developed symptoms of yellowing and desiccation. Conversely, only slight chlorosis spots were observed on the rice leaves co-inoculated with P. ananatis and Xoo (Figure 5B). The lesion length on leaves inoculated with Xoo and sterile water was 15.84 cm, whereas the lesion lengths on leaves co-inoculated with P. ananatis and Xoo ranged from 0.33 cm to 0.77 cm (Figure 6A). P. ananatis strains ZJU1-ZJU18 significantly reduced the lesion length caused by Xoo strain C2, with a disease inhibition rate ranging from 95.14 to 97.92%.

Figure 6
Graphs display lesion lengths in rice plants. Chart A compares lesion lengths across different ZJU treatments with Xoo showing a significant increase. Chart B shows varying Xoo and P. ananatis ratios, with a high lesion length at 0:1. Chart C compares different Xoo strains, all showing high lesion lengths. Chart D contrasts two rice varieties, both with significant lesion lengths when exposed to Xoo alone.

Figure 6. Antibacterial activity of P. ananatis against Xoo in vivo. (A) Antibacterial activity of multiple P. ananatis strains. (B) Effect of inoculation ratio on antibacterial activity. (C) Activity of strain ZJU2 against different Xoo strains. (D) Activity comparison between rice varieties. Statistical differences were analyzed by one-way ANOVA. Different lowercase letters within the same time point and assay indicate significant differences between treatments (p < 0.05).

To determine whether the inhibitory effect of P. ananatis on rice bacterial leaf blight is dependent on the Xoo strain, leaves of the japonica rice cultivar Nipponbare were co-inoculated with P. ananatis strain ZJU2 and different Xoo strains at a 1: 1 ratio. When inoculated alone, Xoo strains C2, PXO99A, and N1 produced lesion lengths of 15.08 cm, 13.43 cm, and 11.78 cm, respectively (Figure 6B). In contrast, co-inoculation with P. ananatis ZJU2 markedly reduced lesion development to 0.33 cm, 0.34 cm, and 0.37 cm, corresponding to disease suppression rates of 97.81, 97.47, and 96.86%, respectively. The results indicated that P. ananatis strain ZJU2 could effectively inhibit rice bacterial leaf blight caused by different Xoo strains in Nipponbare rice. Additionally, to determine whether the inhibitory effect of P. ananatis on rice bacterial leaf blight is influenced by the inoculum ratio of Xoo to P. ananatis, leaves of the japonica rice cultivar Nipponbare were inoculated with Xoo strain C2 and P. ananatis strain ZJU2 at different ratios. When inoculated alone, Xoo strain C2 caused lesions with a mean length of 15.03 cm. In contrast, co-inoculation at Xoo: P. ananatis ratios of 1: 1, 10: 1, and 100: 1 resulted in lesion lengths of 0.45 cm, 0.46 cm, and 4.83 cm, respectively (Figure 6C). The corresponding disease suppression rates were 97.00, 96.94, and 67.87%. The results showed that the lesion inhibition rates of P. ananatis were comparable when the inoculation ratios of Xoo to P. ananatis were 1: 1 and 10: 1, whereas the inhibition rate decreased significantly when the ratio increased sharply to 100: 1.

Furthermore, to determine whether the inhibitory effect of P. ananatis on rice bacterial leaf blight is cultivar-dependent, we performed co-inoculation experiments with the Xoo strain C2 and P. ananatis strain ZJU2. The results showed that in the japonica rice cultivar Nipponbare, the lesion length caused by Xoo alone was 15.18 cm (Figure 6D). In contrast, co-inoculation with Xoo and P. ananatis resulted in a lesion length of only 0.45 cm, corresponding to a disease inhibition rate of 93.23%. Similarly, in the indica rice cultivar 9,311, the lesion length caused by Xoo alone was 12.69 cm, while co-inoculation with Xoo and P. ananatis reduced the lesion length to 0.39 cm, also yielding a disease inhibition rate of 96.93%. The results confirmed that P. ananatis strain ZJU2 exhibited a significant inhibitory effect against Xoo strain C2 across different rice varieties, with the disease inhibition rate exceeding 90.00% in all cases, which indicated that it possesses a broad spectrum antibacterial activity. In conclusion, these results indicated that P. ananatis has strong biocontrol potential and can effectively mitigate the damage inflicted by Xoo on rice.

3.4 Pantoea ananatis inhibits Xoo through nutritional competition in broth

Double-layer plate experiments indicated that while P. ananatis cells produced a faint inhibition zone against Xoo, its cell-free fermentation supernatant failed to generate any zone. This finding prompted further investigation into the underlying ecological interaction mechanisms.

Our study first investigated whether P. ananatis inhibits Xoo via nutrient competition. Growth curve analysis demonstrated that both Xoo and P. ananatis exhibited increased growth over time. At each corresponding time point, the OD600 value of P. ananatis was consistently higher than that of Xoo (Figure 7A). Through calculation, we determined that the fitted growth rate of P. ananatis was 0.140 h−1, while that of Xoo was 0.063 h−1. This demonstrated that the growth rate of P. ananatis is significantly faster than that of Xoo.

Figure 7
Graph A shows the bacterial growth of *Xoo* and *P. ananatis* over 36 hours. *P. ananatis* grows faster, reaching a higher OD\[600\] nm. Graph B displays bacterial counts in various broths; *P. ananatis* consistently shows higher CFU/mL than *Xoo*. Graph C presents flow cytometry plots comparing the bacteria ratios, with percentage distributions indicated in the plots' quadrants.

Figure 7. Growth advantages and nutritional competition of P. ananatis and Xoo in culture medium. (A) Growth curves of Xoo and P. ananatis. (B) The populations of Xoo and P. ananatis of co-culture in NB, NL, and CL broth. (C) Flow cytometry analysis of Xoo and P. ananatis co-cultured at different initial ratios (1: 1, 10: 1, and 100: 1). Statistical differences were analyzed by one-way ANOVA. Different lowercase letters within the same time point and assay indicate significant differences between treatments (p < 0.05).

The growth of Pa (Gen) showed no significant difference compared to the wild-type strain ZJU2, and the growth of Xoo (RFP) was comparable to wild-type strain C2 (Supplementary Figure S4). Co-cultures of Pa (Gen) and Xoo (RFP) were established in different broth, and plate counting was employed to enumerate Xoo and P. ananatis populations (Table 1; Figure 7B). Through calculation, we found that in NB broth, P. ananatis accounted for 99.81% of the total population, while the Xoo population constituted 0.19%. In NL broth, P. ananatis represented 99.99%, with Xoo only making up 0.01%. In CL broth, P. ananatis comprised 98.82%, and Xoo accounted for 1.18%.

Pa(GFP), which showed no significant growth differences compared to the wild-type strain ZJU2, was used as a representative strain in flow cytometry experiments to determine the proportion of P. ananatis in mixed cultures with varying initial ratios of Xoo to P. ananatis (Supplementary Figure S4B). When Xoo and P. ananatis were co-cultured at initial ratios of 1: 1, 10: 1, and 100: 1, the proportions of fluorescent bacteria in the mixed cultures were 83.73, 81.69, and 76.78%, respectively (Figure 7C). Based on these data, the calculated proportions of P. ananatis in the mixed cultures were 99.50, 96.78, and 90.53% for the 1: 1, 10: 1, and 100: 1 initial ratios, respectively. These results consistently supported that P. ananatis inhibits Xoo through nutritional competition in broth. In addition, the spot assay provided visual evidence of a competitive interaction. We observed that the size of the Xoo colony decreased as the distance to the P. ananatis spot diminished (Supplementary Figure S5). This spatial pattern of growth inhibition is consistent with a scenario where P. ananatis, potentially due to its faster growth rate, outcompetes Xoo for limited nutrients in this assay system. It should be noted that the nutrient environment within plant leaves may differ from this in vitro condition.

3.5 Pantoea ananatis inhibits the colonization of Xoo on rice leaves

qPCR analysis showed that the standard curve for absolute quantification of Xoo was y = −4.0034x + 41.004 (R2 = 0.994). qPCR analysis and plate counting experiments confirmed that co-inoculation with P. ananatis significantly reduced the population of Xoo in rice leaves across all time points examined (Figures 8A,B; Table 2). Compared with leaves inoculated solely with Xoo, the infection rate of Xoo on leaves was reduced by 96.78 to 99.00% following co-inoculation with Xoo and P. ananatis. These results indicated that the quantity of Xoo in leaves inoculated solely with Xoo was significantly higher than in leaves co-inoculated with Xoo and P. ananatis at all time points. Thus, P. ananatis significantly inhibits Xoo colonization on rice leaves.

Figure 8
Bar and line graphs comparing the growth of Xoo and Xoo plus P. ananatis over fourteen days. Chart A shows bar heights, with Xoo growth consistently higher than Xoo plus P. ananatis. Chart B shows line graphs depicting a similar trend, with Xoo growth maintaining higher values throughout the incubation period. Both charts indicate statistical significance between groups with letters.

Figure 8. Quantification of Xoo in rice leaves at 1, 3, 7, and 14 dpi with Xoo alone or co-inoculation with P. ananatis. (A) Quantify Xoo through qPCR analysis. (B) Quantify Xoo through plate counting analysis. Statistical differences were analyzed by one-way ANOVA. Different lowercase letters within the same time point and assay indicate significant differences between treatments (p < 0.05).

Table 2
www.frontiersin.org

Table 2. Population dynamics of Xoo in rice leaves and the inhibitory effect of P. ananatis co-inoculation.

3.6 Xoo enhances the colonization of Pantoea ananatis in rice leaves

Based on both qPCR (standard curve: y = −4.767x + 46.209, R2 = 0.989) and plate counting assays, the population of P. ananatis was consistently and significantly higher in leaves co-inoculated with Xoo compared to leaves inoculated with P. ananatis alone at all time points (Figures 9A,B; Table 3). Specifically, the presence of Xoo enhanced the colonization of P. ananatis by 1.99- to 7.96-fold across different time points and detection methods (Table 3).

Figure 9
Panel A shows a bar graph comparing log numbers of P. ananatis under two treatments, Pa and Xoo+Pa, at 1, 3, 7, and 14 days with higher values for Xoo+Pa. Panel B presents a line graph depicting similar data, with Xoo+Pa showing greater increases over time than Pa. Panel C displays four bioluminescence images for 1, 3, 7, and 14 days, each comparing the Pa and Xoo+Pa treatments, where Xoo+Pa consistently exhibits stronger luminescent signals. Panel D is a bar graph showing luminescence intensity (RLU x 10⁶) at four time points, with Xoo+Pa presenting significantly higher values than Pa.

Figure 9. Quantification of P. ananatis in rice leaves at 1, 3, 7, and 14 dpi with P. ananatis alone or co-inoculation with Xoo. (A) Quantify P. ananatis through qPCR analysis. (B) Quantify P. ananatis through plate counting analysis. (C) Luminous signal image. (D) Luminous signal intensity. +: Strong; -: Weak. Scale bar = 1 cm. Statistical differences were analyzed by one-way ANOVA. Different lowercase letters within the same time point and assay indicate significant differences between treatments (p < 0.05).

Table 3
www.frontiersin.org

Table 3. Population dynamics of P. ananatis in rice leaves and the inhibitory effect of Xoo co-inoculation.

In this study, Pa (Lux) was used to evaluate the effect of Xoo inoculation on the population level of P. ananatis in rice leaves. Growth curve analysis revealed no significant difference in growth ability between Pa (Lux) and wild-type P. ananatis strain ZJU2 (Supplementary Figure S4B). The population size of P. ananatis was positively correlated with the bioluminescence intensity from the rice leaves. Over time, the bioluminescence intensity increased significantly in leaves co-inoculated with Xoo and P. ananatis, as well as in those inoculated with P. ananatis alone (Figure 9C). At each time point, the bioluminescence intensity was significantly higher in the co-inoculated leaves than in those inoculated with only P. ananatis (Figure 9D).

3.7 Pantoea ananatis alters the bacterial community structure in rice leaves infected with Xoo

In this study, we found that microbial community structure was significantly influenced by the inoculated strains. At the family level, Enterobacteriaceae, Xanthomonadaceae, and Rhizobiaceae were the predominant bacterial groups in uninoculated groups (C1 and C14). In the Xoo-inoculated groups (X1 and X14), Xanthomonadaceae rapidly became dominant while other bacterial groups significantly declined, thereby indicating the strong inhibitory effect of Xoo on the indigenous community. On the contrary, in the P. ananatis-inoculated groups (P1 and P14), Enterobacteriaceae becoming the absolute dominant group, suggesting its robust colonization ability in leaves. In the co-inoculated with Xoo and P. ananatis groups (XP1 and XP14), the abundance of Xanthomonadaceae was markedly lower than in the Xoo-only inoculated group, demonstrating the sustained inhibitory effect of P. ananatis on Xoo (Figure 10A). At the genus level, different bacterial communities were observed in C1 and C14, with dominant genera of Pseudomonas, Corynebacterium, and Methylobacterium. In the XP1 and XP14, the relative abundances of bacterial groups like Pantoea and Pseudomonas recovered to near-healthy levels (Figure 10B). This indicated that P. ananatis can alleviate the microbial dysbiosis caused by Xoo infection and maintain the stability of the leaf micro-ecosystem.

Figure 10
Bar charts A and B show the relative abundance of different bacterial families in various samples labeled C1, X1, P1, XP1, C14, X14, P14, and XP14. Heatmaps C and D depict hierarchical clustering of bacterial families across the same samples, with a color gradient indicating abundance levels.

Figure 10. Bacterial community composition in rice leaves under different treatments. (A) Family-level species composition diagram. (B) Genus-level species composition diagram. (C) Family-level species composition heatmap. (D) Genus-level species composition heatmap. In the composition heatmap, samples and taxa (families/genera) were clustered via the Unweighted Pair-Group Method with Arithmetic Mean (UPGMA) based on Euclidean distance and Pearson correlation, respectively. C1: 1 d after no bacterial inoculation. X1: 1 d after Xoo inoculation. P1: 1 d after P. ananatis inoculation. XP1: 1 d after co-inoculation with Xoo and P. ananatis. C14: 14 d after no bacterial inoculation. X14: 14 d after Xoo inoculation. P14: 14 d after P. ananatis inoculation. XP14: 14 d after co-inoculation with Xoo and P. ananatis.

Heatmap analysis further corroborated the results from the community composition analysis. In the X1 and X14, the abundance of Enterobacteriaceae and Rhizobiaceae decreased, suggesting that Xoo infection might suppress the growth of certain bacterial groups and lead to community structure imbalance. In the XP1 and XP14, Enterobacteriaceae, Staphylococcaceae, and Burkholderiaceae had higher abundances, with Enterobacteriaceae being dominant (Figure 10C). At the genus level, the relative abundance of Xanthomonas significantly increased in the X1 and X14, while the relative abundance of other genera significantly decreased. Compared to the X1 and X14, the relative abundance of Xanthomonas in the XP1 and XP14 significantly dropped (Figure 10D).

3.8 Pantoea ananatis alters the bacterial community diversity in rice leaves infected with Xoo

Differential bacterial treatments significantly impacted the alpha diversity of bacterial communities in rice leaves. Analysis of Chao1, Shannon, Simpson, and Pielou indices showed that C1 and C14 had the highest species richness and diversity, reflecting the natural abundance and balance of the leaf microbial community (Figure 11A). In contrast, X1 and X14 exhibited a significant decrease across all diversity indices. Specifically, X1’s Chao1, Shannon, Simpson, and Pielou indices decreased by 82.31, 67.60, 37.76, and 54.88%, respectively, compared to C1. Similarly, X14’s Chao1, Shannon, Simpson, and Pielou indices dropped by 76.53, 86.39, 81.44, and 81.48% compared to C14. However, in the XP1 and XP14, all diversity indicators were notably higher than in X1 and X14. For instance, XP1’s Shannon and Simpson indices increased by 86.88 and 47.54%, respectively, compared to X1. Furthermore, XP14’s Shannon and Simpson indices showed even more substantial increases of 378.57 and 377.78%, respectively, compared to X14.

Figure 11
Panel A shows box plots comparing eight groups (C1, X1, P1, XP1, C14, X14, P14, XP14) across four diversity indices: Chao 1, Shannon, Simpson, and Pielou, with p-values indicating statistical significance. Panel B presents a PCoA plot comparing the same groups based on two principal coordinates, PCo1 and PCo2, accounting for 45.4% and 29.9% of variance, respectively. Different colors represent each group.

Figure 11. Alpha diversity and PCoA of bacterial communities in rice leaves under different treatments. (A) Box plots of alpha diversity indices (Chao1, Shannon, Simpson, and Pielou’s evenness). Different panels represent each index. The Kruskal-Wallis test p-value is shown for each index; pairwise significance (Dunns’ test) is marked above plots. (B) PCoA based on Bray-Curtis distances. Percentages in parentheses indicate the proportion of variance explained by each axis. C1: 1 d after no bacterial inoculation. X1: 1 d after Xoo inoculation. P1: 1 d after P. ananatis inoculation. XP1: 1 d after co-inoculation with Xoo and P. ananatis. C14: 14 d after no bacterial inoculation. X14: 14 d after Xoo inoculation. P14: 14 d after P. ananatis inoculation. XP14: 14 d after co-inoculation with Xoo and P. ananatis.

Principal coordinate analysis (PCoA) revealed a clear separation among the sample groups, with the two principal coordinates (PCo1 and PCo2) explaining 45.4 and 29.9% of the total variation, respectively (Figure 11B). Community similarity between the uninoculated control groups (C1 and C14) and all inoculated groups (X1, P1, XP1, X14, P14, and XP14) was low, ranging from 1.34 to 8.52%. This demonstrated that bacterial inoculation significantly altered the resident leaf bacterial community structure. The temporal similarity within treatment groups was 62.15% for the Xoo-inoculated group (X1 vs. X14), 14.76% for the P. ananatis-inoculated group (P1 vs. P14), and 68.15% for the P. ananatis and Xoo co-inoculated group (XP1 vs. XP14). These results indicated that despite temporal shifts, the community composition within each inoculation group maintained a higher degree of consistency compared to the low similarity observed between different treatments. Besides, the community structure of Xoo and P. ananatis co-inoculated leaves more closely resembled that of leaves inoculated solely with P. ananatis rather than with Xoo. Specifically, the similarity between the P1 and XP1 communities was 68.64%, while that between the X1 and XP1 communities was only 18.33%. This disparity became even more pronounced by 14 dpi (75.29% vs. 9.53%).

4 Discussion

Rice bacterial leaf blight poses a serious threat to rice production. Although Xoo is widely recognized as the primary pathogen of rice bacterial leaf blight, recent studies have revealed that some P. ananatis strains not only act as companion pathogens causing similar symptoms but also exhibit biocontrol effects against this disease (Korinsak et al., 2021; Aksoy et al., 2023; Han et al., 2024; Yuan et al., 2024; Jiang et al., 2025). Therefore, this study conducted systematic identification and functional analysis of P. ananatis strains ZJU1-ZJU18 isolated from various regions in China, aiming to clarify their actual role in rice-microbe interactions. The findings not only provided key evidence to resolve the academic controversy of whether P. ananatis acts as a pathogen or a biocontrol agent but also revealed a novel and highly efficient indirect biocontrol mechanism that does not rely on direct antagonism.

Pathogenicity assays revealed that P. ananatis strains ZJU1-ZJU18 did not induce leaf blight symptoms under the tested conditions. While P. ananatis has been reported to cause various symptoms such as rice palea browning (Yan et al., 2010), the ability of strains ZJU1-ZJU18 to induce palea browning was not evaluated in this study. Whether these strains possess the potential to infect rice tissues during the reproductive stage and trigger grain diseases remains an independent and important scientific question, warranting dedicated future studies on rice during its reproductive growth phase.

Genomic analysis indicated that P. ananatis strain ZJU2 carries various virulence-associated factors (e.g., flagella and fimbriae biosynthesis proteins, non-fimbrial adhesins, amylovoran/stewartan-like exopolysaccharides, and pectinolytic enzymes) and mobile genetic elements. Previous studies have shown that these characteristics can facilitate horizontal gene transfer, introducing P. ananatis strain ZJU2 may induce leaf blight symptoms under field conditions (Stice et al., 2018; Yuan et al., 2023). Therefore, before developing these strains as biocontrol agents and deploying these in the field, systematic and long-term risk assessments must be conducted. These should encompass evaluations of its environmental adaptability and genetic stability, as well as indispensable steps such as small-scale field trials, tracking of its environmental fate, and assessments of its impacts on non-target organisms, including other microorganisms and beneficial insects. The plasmids utilized in this study lacked the essential genes for active conjugation, making horizontal gene transfer via this mechanism highly unlikely without helper plasmids. Thus, the risk of resistance gene dissemination to the phyllosphere microbiota under our experimental conditions is considered low. Furthermore, the expression of both antibiotic resistance and fluorescent markers likely carries a metabolic burden. The associated fitness cost may be more significant in the resource-limited phyllosphere or under microbial competition than was captured by our in vitro assays. This limitation highlights a key consideration and defines a clear objective for future work designed to more closely reflect practical environmental conditions.

The beneficial functions of PGP bacteria are attributed to their phosphate-solubilizing ability, siderophore production, and IAA synthesis, which facilitate the acquisition of essential nutrients required for plant growth (Krishnappa et al., 2025). P. ananatis strains ZJU1-ZJU18 exhibited multiple PGP traits. Although these traits were not directly linked to disease resistance in this study, they likely enhance host resistance indirectly by promoting plant growth, thereby increasing the potential of P. ananatis as a multifunctional biocontrol agent.

Results from greenhouse experiments involving the co-inoculation of P. ananatis and Xoo on rice demonstrated that P. ananatis exerted a significant control effect against rice bacterial leaf blight caused by Xoo. However, greenhouse experiments represent merely the first step in screening biocontrol strains, and the high efficacy observed in such trials requires subsequent validation under the more complex microecological conditions of field environments. Double-layer plate test revealed that neither the cells nor the metabolites of these strains produced inhibition zones against Xoo, indicating that their biocontrol mechanism does not rely on the secretion of diffusible antimicrobial compounds. Therefore, the research focus has shifted toward other non-antibacterial mechanisms, such as ecological interference or resource competition (Andongma et al., 2022; Ortiz et al., 2021).

Additionally, this study has not completely excluded the possibility of other non-diffusible mechanisms by P. ananatis, such as direct contact-dependent inhibition or interference with Xoo pathogenicity through quorum sensing disruption. Although frequent cell-to-cell contact occurs in the liquid co-culture system, the current experimental design cannot distinguish the relative contributions of contact inhibition and nutrient competition. Furthermore, P. ananatis may suppress Xoo by modifying the microenvironment, such as local pH or oxygen concentration. This plausible avenue of interference warrants further study.

Previous studies have shown that beneficial bacteria can inhibit pathogen growth through mechanisms such as the secretion of antibacterial compounds, niche competition, and nutrient competition (Shyntum et al., 2019; Wang L. et al., 2023; Leung et al., 2024; Wang X. et al., 2023; Cheng et al., 2025; Romão et al., 2025). This study observed that P. ananatis exhibited a faster growth rate than Xoo under pure culture condition. Flow cytometry analysis further confirmed that, even when the initial inoculum of Xoo was 100 times higher than that of P. ananatis, P. ananatis still accounted for over 90.53% of the total population in the co-culture system. Besides, P. ananatis maintained an absolute growth advantage (> 98.82%) in NL and CL broth. Nutritional competition might be the key factor for P. ananatis to inhibit the growth of Xoo. However, the exact mechanism requires further research.

Plate counting and qPCR analyses consistently demonstrated that P. ananatis significantly inhibited the colonization of Xoo on rice leaves. Compared to leaves inoculated with Xoo, those co-inoculated with Xoo and P. ananatis exhibited a reduction in the Xoo population density of over 96.78%. However, under co-inoculation conditions, there was no order-of-magnitude difference between Xoo and P. ananatis. This suggests that the in vivo advantage of P. ananatis may not stem solely from a higher absolute growth rate. We speculate that Xoo infection might inadvertently create a microenvironment that favors the efficient colonization of P. ananatis at leaf wound sites, thereby suppressing the colonization and expansion of Xoo.

Interestingly, this study found that the presence of Xoo significantly enhanced the colonization of P. ananatis in rice leaves. Based on the established paradigm in plant pathology, the suppression of host basal immunity (PTI) through strategies such as effector secretion is a common evolutionary strategy employed by pathogens to facilitate successful infection and may alter the microenvironment to favor the colonization of other microbes (Xu et al., 2024; Jiang et al., 2025). Therefore, we proposed that Xoo likely promoted the colonization of P. ananatis through multiple interconnected pathways. On the one hand, Xoo may secrete effectors to suppress rice PTI, thereby weakening the plant’s defense against subsequent invasion by P. ananatis and indirectly facilitating its colonization. On the other hand, the leaf cell damage caused by Xoo infection could lead to the leakage of nutrients such as sugars and amino acids, providing an additional nutritional source that supports the proliferation of P. ananatis (Jiang et al., 2025). These Xoo-induced modifications to host physiology and the leaf apoplastic environment are likely key to its facilitative effect on P. ananatis.

The qPCR method employed in this study targets a universal gene of P. ananatis. Therefore, it may theoretically detect both the inoculated Pa (Gen) strain carrying Gen resistance and naturally occurring endogenous P. ananatis populations in rice leaves. However, by incorporating subsequent colony verification using the specific genetic marker of the Pa (Gen) strain, we were able to minimize the likelihood of misattributing endogenous populations to the inoculated strain. Our study revealed that the population of P. ananatis in leaves co-inoculated with Xoo and P. ananatis was 1.99 to 7.96 times higher than that in leaves inoculated solely with P. ananatis. We speculated that Xoo infection may have altered the leaf microenvironment or triggered plant physiological responses, thereby creating more favorable conditions for the proliferation of P. ananatis. The unique interaction between Xoo and P. ananatis not only highlights the complexity of microbial interaction processes but also provides novel insights for developing disease control strategies based on the targeted amplification of beneficial bacterial species.

The structural dynamics of the leaf microbial community have direct or indirect effects on disease development. Community composition analysis and heatmap results demonstrated that P. ananatis can inhibit Xoo proliferation in leaves, alleviate the microbial dysbiosis caused by Xoo infection and maintain the stability of the leaf micro-ecosystem. Alpha diversity analysis results confirmed that Xoo infection markedly reduces the richness and diversity of the leaf microbial community, whereas the introduction of P. ananatis effectively mitigates this decline, helping to change community structure and guide a shift towards a healthier microbial state. PCoA results indicated that P. ananatis exerts a stronger influence than Xoo in modulating the structure of the leaf microbial community. We thought that P. ananatis may preferentially colonize and compete for nutrients to occupy ecological niches, thereby creating a microecological environment unfavorable for Xoo survival, so as to modulate the composition and function of the microbial community, and ultimately achieving sustained and stable biocontrol effects. In future studies, integrating tools such as PICRUSt2 for functional prediction and employing techniques like meta-transcriptomics to validate causal relationships will help position the findings of this research as an initial step for subsequent mechanistic investigations.

5 Conclusion

In conclusion, this study successfully isolated and identified P. ananatis strains ZJU1-ZJU18 and systematically evaluated their biocontrol potential against rice bacterial leaf blight. P. ananatis strains ZJU1-ZJU18 did not induce leaf blight symptoms under the tested conditions and possessed significant PGP potential. Furthermore, their co-inoculation with Xoo significantly suppressed the development of rice bacterial leaf blight. P. ananatis maintains a sustained growth advantage in culture medium, which may be attributed to its strong nutrient competitiveness. Co-inoculation of P. ananatis with Xoo resulted in a significant reduction in the population of Xoo in the leaves, while enhancing the colonization of P. ananatis. 16S amplicon sequencing analysis showed that Xoo infection disrupted the homeostasis of the leaf microbiome, significantly reducing its diversity. Inoculation with P. ananatis can reduce the relative abundance of Xoo in rice leaves. P. ananatis exerts a stronger effect than Xoo in modulating the structure of the leaf microbial community. Our results supported that nutrient competition is a key factor in the inhibition of Xoo by P. ananatis and preliminarily reveals its suppressive effect at the community level, providing a new theoretical foundation and microbial resource for the green and sustainable management of rice bacterial leaf blight.

Data availability statement

The sequence information used in this study can be accessed via the Genbank database (https://www.ncbi.nlm.nih.gov/genbank) using the accession numbers given in Data Sheet 1.

Author contributions

YT: Formal analysis, Data curation, Investigation, Methodology, Conceptualization, Writing – original draft. WL: Validation, Writing – review & editing, Formal analysis. JZ: Writing – review & editing, Formal analysis, Validation. YS: Validation, Formal analysis, Writing – review & editing. JL: Writing – review & editing, Supervision, Funding acquisition, Conceptualization, Project administration, Methodology, Formal analysis. MI: Investigation, Writing – review & editing, Formal analysis, Data curation. AA: Formal analysis, Writing – review & editing, Data curation, Investigation. TA: Data curation, Investigation, Writing – review & editing, Formal analysis. CY: Conceptualization, Project administration, Writing – review & editing, Supervision, Methodology, Formal analysis, Funding acquisition. BL: Supervision, Writing – review & editing, Conceptualization, Funding acquisition, Formal analysis, Project administration, Methodology.

Funding

The author(s) declared that financial support was received for this work and/or its publication. The work is partially supported by Zhejiang Province “San Nong Jiu Fang” Science and Technology Plan Project (2025SNJF027), State Key Laboratory for Quality and Safety of Agro‑products (2021DG700024-KF202508). Additionally, this study is supported via funding from Prince Sattam bin Abdulaziz University Project Number (PSAU/2025/R/1447).

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that Generative AI was used in the creation of this manuscript. During the preparation of this work the author(s) used ChatGpt tool to improve language and readability. After using this tool, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmicb.2026.1722838/full#supplementary-material

Footnotes

References

Ahmed, T., Luo, J., Noman, M., Ijaz, M., Wang, X., Masood, H., et al. (2023). Microbe-mediated nanoparticle intervention for the management of plant diseases. Crop Health 1:3. doi: 10.1007/s44297-023-00006-9

Crossref Full Text | Google Scholar

Aksoy, H. M., Boluk, E., Kaya, Y., and Marakli, S. (2023). The effect of leaf blight disease of rice caused by Pantoea ananatis on Nikita, Osr30 and RIRE1 retrotransposons’ movements. J. Plant Pathol. 105, 1629–1636. doi: 10.1007/s42161-023-01514-x

Crossref Full Text | Google Scholar

Andongma, A. A., Whitten, M. M. A., Del Sol, R., Hitchings, M., and Dyson, P. J. (2022). Bacterial competition influences the ability of symbiotic bacteria to colonize western flower thrips. Front. Microbiol. 13:883891. doi: 10.3389/fmicb.2022.883891,

PubMed Abstract | Crossref Full Text | Google Scholar

Arayaskul, N., Poompouang, S., Lithanatudom, P., and Lithanatudom, S. K. (2020). First report of a leaf blight in rice (Oryza sativa) caused by Pantoea ananatis and Pantoea stewartii in Thailand. Plant Dis. 104, 562–563. doi: 10.1094/PDIS-05-19-1038-PDN

Crossref Full Text | Google Scholar

Azizi, M. M. F., Ismail, S. I., Ina-Salwany, M. Y., Hata, E. M., and Zulperi, D. (2020). The emergence of Pantoea species as a future threat to global rice production. J Plant Protect Res 60, 327–335. doi: 10.24425/jppr.2020.133958

Crossref Full Text | Google Scholar

Brady, C., Cleenwerck, I., Venter, S., Vancanneyt, M., Swings, J., and Coutinho, T. (2008). Phylogeny and identification of Pantoea species associated with plants, humans and the natural environment based on multilocus sequence analysis (MLSA). Syst. Appl. Microbiol. 31, 447–460. doi: 10.1016/j.syapm.2008.09.004,

PubMed Abstract | Crossref Full Text | Google Scholar

Cao, Y., Zhang, Y., Chen, Y., Yu, N., Liaqat, S., Wu, W., et al. (2021). OsPG1 encodes a polygalacturonase that determines cell wall architecture and affects resistance to bacterial blight pathogen in rice. Rice 14:36. doi: 10.1186/s12284-021-00478-9,

PubMed Abstract | Crossref Full Text | Google Scholar

Cheng, R., Ke, T., Gui, F., Li, J., Zhang, X., Vílchez, J., et al. (2025). drSMALL: database for disease resistance-shaping small molecules derived from the plant microbiome. Crop Health 3:2. doi: 10.1007/s44297-025-00042-7

Crossref Full Text | Google Scholar

Chumpol, A., Monkham, T., Saepaisan, S., Sanitchon, J., Falab, S., and Chankaew, S. (2022). Phenotypic broad spectrum of bacterial blight disease resistance from Thai indigenous upland rice germplasms implies novel genetic resource for breeding program. Agronomy 12:1930. doi: 10.3390/agronomy12081930

Crossref Full Text | Google Scholar

Dahiya, P., Kumar, P., Rani, S., Dang, A. S., and Suneja, P. (2024). Comparative genomic and functional analyses for insights into Pantoea agglomerans strains adaptability in diverse ecological niches. Curr. Microbiol. 81:254. doi: 10.1007/s00284-024-03763-0,

PubMed Abstract | Crossref Full Text | Google Scholar

De Armas, S., Galván, G. A., Lapaz, M. I., González-Barrios, P., Vicente, E., Pianzzola, M. J., et al. (2022). Phylogeny and identification of Pantoea species associated with bulb rot and bacterial leaf blight of onion crops in Uruguay. Plant Dis. 106, 1216–1225. doi: 10.1094/PDIS-06-21-1140-RE,

PubMed Abstract | Crossref Full Text | Google Scholar

Duan, G., Liu, X., Zhang, S., Chai, M., Peng, Z., Lin, Z., et al. (2025). An emerging bacterial leaf disease in rice caused by Pantoea ananatis and Pantoea eucalypti in Northeast China. Microorganisms 13:1376. doi: 10.3390/microorganisms13061376,

PubMed Abstract | Crossref Full Text | Google Scholar

Duku, C., Sparks, A. H., and Zwart, S. J. (2016). Spatial modelling of rice yield losses in Tanzania due to bacterial leaf blight and leaf blast in a changing climate. Clim. Chang. 135, 569–583. doi: 10.1007/s10584-015-1580-2

Crossref Full Text | Google Scholar

Gnanamanickam, S. S., Priyadarisini, V. B., Narayanan, N. N., Vasudevan, P., and Kavitha, S. (1999). An overview of bacterial blight disease of rice and strategies for its management. Curr. Sci. 77, 1435–1444.

Google Scholar

Goris, J., Konstantinidis, K. T., Klappenbach, J. A., Coenye, T., Vandamme, P., and Tiedje, J. M. (2007). DNA-DNA hybridization values and their relationship to whole-genome sequence similarities. Int. J. Syst. Evol. Microbiol. 57, 81–91. doi: 10.1099/ijs.0.64483-0

Crossref Full Text | Google Scholar

Guedj-Dana, Y., Cohen-Gihon, I., Israeli, O., Shifman, O., Aminov, T., Rotem, S., et al. (2022). Whole genome sequencing and taxonomic profiling of two Pantoea sp. isolated from environmental samples in Israel. BMC Genom Data 23:31. doi: 10.1186/s12863-022-01049-7,

PubMed Abstract | Crossref Full Text | Google Scholar

Han, Z., Huang, D., Wang, M., Xie, H., and Wang, J. (2024). First report of bacterial leaf streak of rice caused by Pantoea ananatis in Guangdong province, China. Plant Dis 108:1881. doi: 10.1094/PDIS-02-24-0421-PDN

Crossref Full Text | Google Scholar

He, Y. W., Law, J. W. F., Azad, S. M., Hu, W. D., Song, K., Chua, K. O., et al. (2025). Identification and genomic analyses of a novel actinobacterium Streptomyces shaowuensis sp. nov. with biocontrol potential for rice bacterial blight. Phytopathol Res 7:24. doi: 10.1186/s42483-025-00313-9

Crossref Full Text | Google Scholar

Islam, M. R., Chowdhury, R., Roy, A. S., Islam, M. N., Mita, M. M., Bashar, S., et al. (2023). Native Trichoderma induced the defense-related enzymes and genes in rice against Xanthomonas oryzae pv. Oryzae (Xoo). Plants 12:1864. doi: 10.3390/plants12091864,

PubMed Abstract | Crossref Full Text | Google Scholar

Jiang, H., Xu, X., Lv, L., Huang, X., Ahmed, T., Tian, Y., et al. (2025). Host metabolic alterations mediate phyllosphere microbes defense upon Xanthomonas oryzae pv oryzae infection. J. Agric. Food Chem. 73, 249–259. doi: 10.1021/acs.jafc.4c09178,

PubMed Abstract | Crossref Full Text | Google Scholar

Kini, K., Agnimonhan, R., Dossa, R., Silué, D., and Koebnik, R. (2021). Genomics-informed multiplex PCR scheme for rapid identification of rice-associated bacteria of the genus Pantoea. Plant Dis. 105, 2389–2394. doi: 10.1094/PDIS-07-20-1474-RE,

PubMed Abstract | Crossref Full Text | Google Scholar

Komaki, H. (2022). Resolution of housekeeping gene sequences used in MLSA for the genus Streptomyces and reclassification of Streptomyces anthocyanicus and Streptomyces tricolor as heterotypic synonyms of Streptomyces violaceoruber. Int. J. Syst. Evol. Microbiol. 72:005370. doi: 10.1099/ijsem.0.005370,

PubMed Abstract | Crossref Full Text | Google Scholar

Korinsak, S., Darwell, C. T., Wanchana, S., Praphaisal, L., Korinsak, S., Thunnom, B., et al. (2021). Identification of bacterial blight resistance loci in rice (Oryza sativa L.) against diverse Xoo Thai strains by genome-wide association study. Plants 10:518. doi: 10.3390/plants10030518,

PubMed Abstract | Crossref Full Text | Google Scholar

Krishnappa, C., Balamurugan, A., Velmurugan, S., Kumar, S., Sampathrajan, V., Kundu, A., et al. (2024). Rice foliar-adapted Pantoea species: promising microbial biostimulants enhancing rice resilience against foliar pathogens, Magnaporthe oryzae and Xanthomonas oryzae pv. Oryzae. Microbial Pathog 186:106445. doi: 10.1016/j.micpath.2023.106445,

PubMed Abstract | Crossref Full Text | Google Scholar

Krishnappa, C., Javed, M., Balamurugan, A., Kumar, S., Velmurugan, S., Kundu, A., et al. (2025). Exometabolome of Pantoea targets pathogen associated scytalone dehydratase and XopQ for suppression of foliar blast and bacterial blight in rice. Int. J. Biol. Macromol. 318:145079. doi: 10.1016/j.ijbiomac.2025.145079,

PubMed Abstract | Crossref Full Text | Google Scholar

Leung, P. B., Matanza, X. M., Roche, B., Ha, K. P., Cheung, H. C., Appleyard, S., et al. (2024). Shigella sonnei utilises colicins during inter- bacterial competition. Microbiology 170:001434. doi: 10.1099/mic.0.001434,

PubMed Abstract | Crossref Full Text | Google Scholar

Liu, F., Hu, M., Tan, X., Xue, Y., Li, C., Wang, S., et al. (2023). Pseudomonas chlororaphis L5 and Enterobacter asburiae L95 biocontrol Dickeya soft rot diseases by quenching virulence factor modulating quorum sensing signal. Microb. Biotechnol. 16, 2145–2160. doi: 10.1111/1751-7915.14351,

PubMed Abstract | Crossref Full Text | Google Scholar

Luna, E., Lang, J., McClung, A., Wamishe, Y., Jia, Y., and Leach, J. E. (2023). First report of rice bacterial leaf blight disease caused by Pantoea ananatis in the United States. Plant Dis. 107:2214. doi: 10.1094/PDIS-08-22-2014-PDN

Crossref Full Text | Google Scholar

Lv, L., Luo, J., Ahmed, T., Zaki, H. E. M., Tian, Y., Shahid, M. S., et al. (2022). Beneficial effect and potential risk of Pantoea on rice production. Plants 11:2608. doi: 10.3390/plants11192608,

PubMed Abstract | Crossref Full Text | Google Scholar

Noman, M., Ahmed, T., Wang, J., Ijaz, M., Shahid, M., Islam, M., et al. (2023). Nano-enabled crop resilience against pathogens: potential, mechanisms and strategies. Crop Health 1:15. doi: 10.1007/s44297-023-00015-8

Crossref Full Text | Google Scholar

Ooi, Y. S., Mohamed Nor, N. M. I., Furusawa, G., Tharek, M., and Ghazali, A. H. (2022). Application of bacterial endophytes to control bacterial leaf blight disease and promote rice growth. Plant Pathol. J. 38, 490–502. doi: 10.5423/PPJ.OA.01.2022.0014,

PubMed Abstract | Crossref Full Text | Google Scholar

Ortiz, A., Vega, N. M., Ratzke, C., and Gore, J. (2021). Interspecies bacterial competition regulates community assembly in the C. elegans intestine. ISME J. 15, 2131–2145. doi: 10.1038/s41396-021-00910-4,

PubMed Abstract | Crossref Full Text | Google Scholar

Ramprasad, E., Rani, C. V. D., Neeraja, C. N., Padmavathi, G., Jagadeeshwar, R., Anjali, C., et al. (2024). Understanding the nature of blast resistance in combined bacterial leaf blight and blast gene pyramided lines of rice variety tellahamsa. Mol. Biol. Rep. 51:619. doi: 10.1007/s11033-024-09549-8,

PubMed Abstract | Crossref Full Text | Google Scholar

Ritbamrung, O., Inthima, P., Ratanasut, K., Sujipuli, K., Rungrat, T., and Buddhachat, K. (2025). Evaluating Xanthomonas oryzae pv. Oryzae (Xoo) infection dynamics in rice for distribution routes and environmental reservoirs by molecular approaches. Sci. Rep. 15:1408. doi: 10.1038/s41598-025-85422-3,

PubMed Abstract | Crossref Full Text | Google Scholar

Romão, I. R., do Carmo Gomes, J., Silva, D., and Vilchez, J. I. (2025). The seed microbiota from an application perspective: an underexplored frontier in plant–microbe interactions. Crop Health 3:12. doi: 10.1007/s44297-025-00051-6

Crossref Full Text | Google Scholar

Shyntum, D. Y., Nkomo, N. P., Shingange, N. L., Gricia, A. R., Bellieny-Rabelo, D., and Moleleki, L. N. (2019). The impact of type VI secretion system, bacteriocins and antibiotics on bacterial competition of Pectobacterium carotovorum subsp. brasiliense and the regulation of carbapenem biosynthesis by iron and the ferric-uptake regulator. Front. Microbiol. 10:2379. doi: 10.3389/fmicb.2019.02379,

PubMed Abstract | Crossref Full Text | Google Scholar

Stice, S. P., Stumpf, S. D., Gitaitis, R. D., Kvitko, B. H., and Dutta, B. (2018). Pantoea ananatis genetic diversity analysis reveals limited genomic diversity as well as accessory genes correlated with onion pathogenicity. Front. Microbiol. 9:184. doi: 10.3389/fmicb.2018.00184,

PubMed Abstract | Crossref Full Text | Google Scholar

Suleimanova, A. D., Itkina, D. L., Pudova, D. S., and Sharipova, M. R. (2021). Identification of Pantoea phytate-hydrolyzing rhizobacteria based on their phenotypic features and multilocus sequence analysis (MLSA). Microbiology 90, 87–95. doi: 10.1134/S0026261721010112

Crossref Full Text | Google Scholar

Sumuni, S. M., Kaur, R., Kaur, R., Khanna, R., Kaur, K., Lore, J. S., et al. (2024). Multivariate analysis for morpho-physiological and milling traits along with molecular profiling of known bacterial blight resistance genes in advanced breeding lines of rice. Cereal Res. Commun. 52, 759–775. doi: 10.1007/s42976-023-00412-3

Crossref Full Text | Google Scholar

Sun, L., Cheng, L., Ma, Y., Lei, P., Wang, R., Gu, Y., et al. (2022). Exopolysaccharides from Pantoea alhagi NX-11 specifically improve its root colonization and rice salt resistance. Int. J. Biol. Macromol. 209, 396–404. doi: 10.1016/j.ijbiomac.2022.04.015,

PubMed Abstract | Crossref Full Text | Google Scholar

Tambong, J. T. (2019). Taxogenomics and systematics of the genus Pantoea. Front. Microbiol. 10:2463. doi: 10.3389/fmicb.2019.02463,

PubMed Abstract | Crossref Full Text | Google Scholar

Tariq, M., Hasnain, N., Rasul, I., Asad, M. A., Javed, A., Rashid, K., et al. (2023). Reconnoitering the capabilities of nodule endophytic Pantoea dispersa for improved nodulation and grain yield of chickpea (Cicer arietinum L.). World J. Microbiol. Biotechnol. 39:85. doi: 10.1007/s11274-023-03525-3,

PubMed Abstract | Crossref Full Text | Google Scholar

Tian, S., Xu, Y., Zhong, Y., Qiao, Y., Wang, D., Wu, L., et al. (2024). Exploring the organic acid secretion pathway and potassium solubilization ability of Pantoea vagans ZHS-1 for enhanced rice growth. Plants 13:1945. doi: 10.3390/plants13141945,

PubMed Abstract | Crossref Full Text | Google Scholar

Timilsina, S., Potnis, N., Newberry, E. A., Liyanapathiranage, P., Iruegas-Bocardo, F., White, F. F., et al. (2020). Xanthomonas diversity, virulence and plant-pathogen interactions. Nat. Rev. Microbiol. 18, 415–427. doi: 10.1038/s41579-020-0361-8,

PubMed Abstract | Crossref Full Text | Google Scholar

Toh, W. K., Loh, P. C., and Wong, H. L. (2019). First report of leaf blight of rice caused by Pantoea ananatis and Pantoea dispersa in Malaysia. Plant Dis. 103, 1764–1764. doi: 10.1094/PDIS-12-18-2299-PDN

Crossref Full Text | Google Scholar

Walterson, A. M., and Stavrinides, J. (2015). Pantoea: insights into a highly versatile and diverse genus within the Enterobacteriaceae. FEMS Microbiol. Rev. 39, 968–984. doi: 10.1093/femsre/fuv027,

PubMed Abstract | Crossref Full Text | Google Scholar

Wang, L., Fang, H., Xue, Z., De, J., and Guo, X. (2023). Agrochemical exposure-induced seed microbiome response in barley. Crop Health 1:16. doi: 10.1007/s44297-023-00013-w

Crossref Full Text | Google Scholar

Wang, X., Wang, J., Liu, S., Guo, J., Fang, F., Chen, Y., et al. (2023). Mechanisms of survival mediated by the stringent response in Pseudomonas aeruginosa under environmental stress in drinking water systems: nitrogen deficiency and bacterial competition. J. Hazard. Mater. 448:130941. doi: 10.1016/j.jhazmat.2023.130941,

PubMed Abstract | Crossref Full Text | Google Scholar

Wang, P., Zhang, J., Dong, L., Fu, Y., Guo, Q., and Ma, P. (2025). First report of Pantoea dispersa causing strawberry root rot in China. Plant Dis. 109:1372. doi: 10.1094/PDIS-11-24-2486-PDN

Crossref Full Text | Google Scholar

Xie, L., Liu, L., Luo, Y., Rao, X., Di, Y., Liu, H., et al. (2023). Corrigendum: complete genome sequence of biocontrol strain Bacillus velezensis YC89 and its biocontrol potential against sugarcane red rot. Front. Microbiol. 14:1235695. doi: 10.3389/fmicb.2023.1235695,

PubMed Abstract | Crossref Full Text | Google Scholar

Xu, M., Xu, J., and Liu, H. (2024). Strategies of plant pathogenic fungi to inhibit chitin-triggered plant immune responses. Acta Phytopathol Sin 54, 15–18. doi: 10.13926/j.cnki.apps.000870

Crossref Full Text | Google Scholar

Xu, C., Zhong, L., Huang, Z., Li, C., Lian, J., Zheng, X., et al. (2022). Real-time monitoring of Ralstonia solanacearum infection progress in tomato and Arabidopsis using bioluminescence imaging technology. Plant Methods 18:7. doi: 10.1186/s13007-022-00841-x,

PubMed Abstract | Crossref Full Text | Google Scholar

Xue, Y., Hu, M., Chen, S., Hu, A., Li, S., Han, H., et al. (2021). Enterobacter asburiae and Pantoea ananatis causing rice bacterial blight in China. Plant Dis. 105, 2078–2088. doi: 10.1094/PDIS-10-20-2292-RE,

PubMed Abstract | Crossref Full Text | Google Scholar

Yan, H., Yu, S., Xie, G., Fang, W., Su, T., and Li, B. (2010). Grain discoloration of rice caused by Pantoea ananatis (synonym Erwinia uredovora) in China. Plant Dis. 94:482. doi: 10.1094/PDIS-94-4-0482B. 30754503,

PubMed Abstract | Crossref Full Text | Google Scholar

Yang, F., Zhang, J., Zhang, H., Ji, G., Zeng, L., Li, Y., et al. (2020). Bacterial blight induced shifts in endophytic microbiome of rice leaves and the enrichment of specific bacterial strains with pathogen antagonism. Front. Plant Sci. 11:963. doi: 10.3389/fpls.2020.00963,

PubMed Abstract | Crossref Full Text | Google Scholar

Yu, L., Yang, C., Ji, Z., Zeng, Y., Liang, Y., and Hou, Y. (2022). First report of new bacterial leaf blight of rice caused by Pantoea ananatis in Southeast China. Plant Dis. 106, 310–310. doi: 10.1094/PDIS-05-21-0988-PDN

Crossref Full Text | Google Scholar

Yuan, J., He, S., Zhang, J., Meng, H., Wang, B., Wei, L., et al. (2024). Identification of an endophytic Pantoea ananatis strain XP-1 with antagonistic effect to Xanthomonas oryzae pv. Oryzicola and growth-promoting effect on rice seedlings. Acta Phytopathol Sin 54, 808–818. doi: 10.13926/j.cnki.apps.001626

Crossref Full Text | Google Scholar

Yuan, T., Huang, Y., Luo, L., Wang, J., Li, J., Chen, J., et al. (2023). Complete genome sequence of Pantoea ananatis strain LCFJ-001 isolated from bacterial wilt mulberry. Plant Dis. 107, 2500–2505. doi: 10.1094/PDIS-10-22-2473-A,

PubMed Abstract | Crossref Full Text | Google Scholar

Zhang, D., He, W., Shao, Z., Ahmed, I., Zhang, Y., Li, W., et al. (2023). EasyCGTree: a pipeline for prokaryotic phylogenomic analysis based on core gene sets. BMC Bioinformatics 24:390. doi: 10.1186/s12859-023-05527-2,

PubMed Abstract | Crossref Full Text | Google Scholar

Zhang, Y., Zhu, Z., Qin, T., Li, X., Yu, R., Tang, Z., et al. (2024). Whole genome sequencing and comparative genomic analysis of Pseudomonas aeruginosa SF416, a potential broad-spectrum biocontrol agent against Xanthomonas oryzae pv. Oryzae. Microorganisms 12:2263. doi: 10.3390/microorganisms12112263,

PubMed Abstract | Crossref Full Text | Google Scholar

Keywords: biological control, microbial community, nutrient competition, Pantoea ananatis, rice bacterial leaf blight, Xanthomonas oryzae pv. oryzae

Citation: Tian Y, Lei W, Zhang J, Shen Y, Lu J, Ijaz M, Alrafaie A, Ahmed T, Yan C and Li B (2026) Mechanism of Pantoea ananatis in the biocontrol of rice bacterial leaf blight. Front. Microbiol. 17:1722838. doi: 10.3389/fmicb.2026.1722838

Received: 11 October 2025; Revised: 11 January 2026; Accepted: 13 January 2026;
Published: 04 February 2026.

Edited by:

Iftikhar Ahmed, National Agricultural Research Center, Pakistan

Reviewed by:

Prabhu B. Patil, Institute of Microbial Technology (CSIR), India
Harekrushna Swain, Eastern Regional Center, India
Hang Dinh, Vietnam National University, Vietnam

Copyright © 2026 Tian, Lei, Zhang, Shen, Lu, Ijaz, Alrafaie, Ahmed, Yan and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Jianfei Lu, MTA5NTIzMjcxMkBxcS5jb20=; Chengqi Yan, eWFuY2hlbmdxaUAxNjMuY29t; Bin Li, bGliaW4wNTcxQHpqdS5lZHUuY24=

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.