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Bacterial seed endophyte shapes disease resistance in rice


Cereal crop production is severely affected by seed-borne bacterial diseases across the world. Locally occurring disease resistance in various crops remains elusive. Here, we have observed that rice plants of the same cultivar can be differentiated into disease-resistant and susceptible phenotypes under the same pathogen pressure. Following the identification of a seed-endophytic bacterium as the resistance-conferring agent, integration of high-throughput data, gene mutagenesis and molecular interaction assays facilitated the discovery of the underlying mode of action. Sphingomonas melonis that is accumulated and transmitted across generations in disease-resistant rice seeds confers resistance to disease-susceptible phenotypes by producing anthranilic acid. Without affecting cell growth, anthranilic acid interferes with the sigma factor RpoS of the seed-borne pathogen Burkholderia plantarii, probably leading to impairment of upstream cascades that are required for virulence factor biosynthesis. The overall findings highlight the hidden role of seed endophytes in the phytopathology paradigm of ‘disease triangles’, which encompass the plant, pathogens and environmental conditions. These insights are potentially exploitable for modern crop cultivation threatened by globally widespread bacterial diseases.

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Fig. 1: Distinguishable phenotypes of rice seedlings (cv. Zhongzao 39) from different geographical origins in disease resistance.
Fig. 2: Prevalent bacterial genera in the seed endosphere of rice.
Fig. 3: Characterization of the seed endophyte conferring disease resistance.
Fig. 4: Screening and identification of the essential signalling molecule produced by Sphingomonas for conferring disease resistance.
Fig. 5: Ecological function of Sphingomonas-derived AA.
Fig. 6: Transcriptome profiling and SPR analysis of interference caused by AA on cellular functioning of Bp.

Data availability

All raw sequence data have been deposited in the Sequence Read Archive of NCBI. Bp and Sm genomes were deposited under BioProject accessions PRJNA323430 and PRJNA224116, respectively. Rice seed endosphere, bulk soil and rhizosphere microbiome data from the initial microbiome profiling were deposited under the accession PRJNA534278. Data obtained in the frame of the detailed microbiome analysis of bacterial and fungal communities were deposited under accession PRJEB39399. Transcriptome datasets were deposited under accession PRJNA534192. The 16S rRNA gene sequence of Sm was deposited under accession LC500070 in NCBI Genbank. The AA-associated pathway is available under accession CP023705.1 in the KEGG Compound Database. The reference sequence that was used for Bp genome assembly is available under RefSeq assembly accession GCF_001411805.1 in the NCBI Genbank. All other raw data for all figures and tables are available from the corresponding authors upon reasonable request. Source data are provided with this paper.


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This work was supported by National Key R&D Programme of China (grant nos. 2017YFE0102200, 2017YFD0202100 and 2016YFD0200804), Programme for High-Level Talents Cultivation of Zhejiang University, National Natural Science Foundation of China (grant no. 31501684), Zhejiang Provincial Key Research and Development Programme of China (grant no. 2015C02019) and Zhejiang Provincial Natural Science Foundation of China (grant no. LQ16C140001). We are also grateful to Z. Lv, B. Li and D. Xiang for providing microbial strains and plasmids as well as their valuable suggestions for molecular biology experiments; X. Chen for his support by provision of chemical reagents; Z. Ge and J. Pan for their assistance with NMR and MS analyses; and P. Shen, Z. Shang and Y. Wang for their kind help and advice during field experiments. We thank Personal Biotechnology and Magigene for their high-throughput sequencing services.

Author information

Authors and Affiliations



H.M., M.W. and T.C. designed the research. H.M., T.C., X.F., P.K., J.D., Y.W., S.C., K.Q., Y.W. and M.W performed the research. M.W., H.M., T.C., P.K., X.F., B.M., S.C., Y.H., S.W., Y.W., G.Z., K.Q. and Y.W. analysed data. M.W., H.M., T.C. and G.B. wrote the paper.

Corresponding authors

Correspondence to Tomislav Cernava or Mengcen Wang.

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Peer review information Nature Plants thanks Nathan Vannier and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Microbiome analyses of rice seeds from different harvest years.

Bacterial (a-d) and fungal (e,f) community structures were analysed in the seed endosphere of rice. Geographical origins of the rice seeds are indicated by S2, S3, S5, and S8. Initial microbiome profiling with seeds from the growing season in 2016 (3 replicates per region; each replicate consisted of 100 mg homogenates obtained from 10 seedlings) was visualized on bacterial phylum (a) and genus (c) level. The same data processing was applied for the detailed analysis and subsequent visualization of seed microbiomes from the growing season in 2019 on bacterial phylum (b) and genus (d) level (12 replicates per region; each replicate consisted of 100 mg homogenates obtained from 10 seedlings). A complementary analysis of the fungal community shows the community on phylum (e) and genus (f) level.

Extended Data Fig. 2 Capacity of Sphingomonas melonis (Sm) to confer disease resistance to representative susceptible cultivars of rice.

For the three important rice subgroups, Oryza sativa subsp. xian, Oryza sativa subsp. geng, and hybrid rice, 15 representative susceptible cultivars (5 cultivars per subgroup) were primed with Sm (106 CFU/mL) and tested for their resistance against Bp by comparison of growth performance of culm height after 5-d growth (10 rice seedlings per cultivar). Values are means ± SD (shown as error bars; n = 10 seedlings). P value, Student’s t-test (two-tailed), shown on the top of the paired columns.

Extended Data Fig. 3 Modelling of potential interactions of RpoS with different anthranilic acid (AA) isomers.

The interaction between anthranilic acid (a), meta-anthranilic acid (b) and para-anthranilic acid (c), respectively with RpoS of B. plantarii were analysed with molecular docking experiments. Illustrations of the interaction between AA and RpoS by molecular docking (left panel), and putative binding sites and modes of AA stabilization by amino acid residues of RpoS (right panel) are shown.

Extended Data Fig. 4 Microbiome profiling of bulk soil, seed endosphere, and rhizosphere in 2016.

The bulk soil (a), seed endosphere (b), and the rhizosphere (c) during the growing season in 2016 were collected in the investigated rice paddies. S2, S3, S5, and S8 indicates the geographical origins of the samples. The taxonomy was assessed at bacterial genus level whenever possible; when taxonomy was only assignable at bacterial class level, ‘c’ was added in front of the Latin name.

Extended Data Fig. 5 Chemical structures of the herbicides that were detected in the rice paddies located at the four investigated regions in Zhejiang Province.

The labels S2, S3, S5, and S8 indicate the geographical locations of the paddies where the herbicides were detected. The locations correspond to the sampling locations where the rice seeds were collected in the growing seasons 2016 and 2019.

Supplementary information

Supplementary Information

Supplementary methods, Tables 1–8, Figs. 1–30 and references.

Reporting Summary

Supplementary Data 1

Analysis of differential occurrence of bacterial ASVs in the seed endosphere of rice.

Supplementary Data 2

Comparison of different Sphingomonas species and strains on genome level.

Supplementary Data 3

ASV tables from all microbiome datasets.

Supplementary Data 4

List of significantly upregulated genes following AA treatment.

Supplementary Data 5

List of significantly downregulated genes following AA treatment.

Supplementary Data 6

Enriched KEGG pathways with significantly downregulated genes.

Source data

Source Data Fig. 1f

Unprocessed gels.

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Matsumoto, H., Fan, X., Wang, Y. et al. Bacterial seed endophyte shapes disease resistance in rice. Nat. Plants 7, 60–72 (2021).

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