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Phyllosphere microbiome induces host metabolic defence against rice false-smut disease

Nature Microbiology volume 8, pages 1419–1433 (2023)Cite this article

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Abstract

Mutualistic interactions between host plants and their microbiota have the potential to provide disease resistance. Most research has focused on the rhizosphere, but it is unclear how the microbiome associated with the aerial surface of plants protects against infection. Here we identify a metabolic defence underlying the mutualistic interaction between the panicle and the resident microbiota in rice to defend against a globally prevalent phytopathogen, Ustilaginoidea virens, which causes false-smut disease. Analysis of the 16S ribosomal RNA gene and internal transcribed spacer sequencing data identified keystone microbial taxa enriched in the disease-suppressive panicle, in particular Lactobacillus spp. and Aspergillus spp. Integration of these data with primary metabolism profiling, host genome editing and microbial isolate transplantation experiments revealed that plants with these taxa could resist U. virens infection in a host branched-chain amino acid (BCAA)-dependent manner. Leucine, a predominant BCAA, suppressed U. virens pathogenicity by inducing apoptosis-like cell death through H2O2 overproduction. Additionally, preliminary field experiments showed that leucine could be used in combination with chemical fungicides with a 50% reduction in dose but similar efficacy to higher fungicide concentrations. These findings may facilitate protection of crops from panicle diseases prevalent at a global scale.

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Fig. 1: Analysis of panicle microbiome in diseased and disease-suppressive rice plants.
Fig. 2: Profiling of the local metabolism in microbiota structure-specific rice panicles.
Fig. 3: Dissection of the complexity of interactions among branched amino acids, microbiota and disease suppression in rice panicles.
Fig. 4: Characterization of cellular dysfunction in U. virens upon exposure to branched amino acids.
Fig. 5: Transcriptome profiling-guided analyses of leucine-induced cell dysfunction in U. virens.

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Data availability

All raw sequence data were deposited in the Sequence Read Archive of NCBI (https://www.ncbi.nlm.nih.gov/sra). Microbiome data were deposited under the accession PRJNA540087 (panicle fungal community), PRJNA830622 (panicle bacterial community), PRJNA830632 (rhizosphere fungal community) and PRJNA830626 (rhizosphere bacterial community). SILVA (release 138, https://www.arb-silva.de/no_cache/download/archive/release_138.1/ARB_files/) and the NCBI taxonomy database (https://www.ncbi.nlm.nih.gov/taxonomy) were used for analysis of bacterial 16S rRNA gene and fungal ITS sequences, respectively. Transcriptome data were deposited under the accession PRJNA539859 and the reads were mapped to the U. virens reference genome sequence with refSeq assembly accession GCF_000687475.1. Source data are provided with this paper.

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Acknowledgements

This study was supported by the National Natural Science Foundation of China (32122074, U21A20219), National Key R&D Program of China (2021YFE0113700), the Fundamental Research Funds for the Central Universities (2021FZZX001-31), the Strategic Research on ‘Plant Microbiome and Agroecosystem Health’ (2020ZL008, Cao Guangbiao High Science and Technology Foundation) and the Program for High-level Talents Cultivation and Global Partnership Fund (Zhejiang University). We thank P. Shen (Office of Xiaoshan Agricultural Comprehensive Development Zone and Management Committee, Hangzhou, China) for assistance in field trials; Y. Kou, X. Cao and H. Shi (China National Rice Research Institute) for assistance in genetic manipulation of U. virens; X. Feng (Agricultural Experiment Station, Zhejiang University) for assistance in microscopic analysis; and Y. Gafforov (Uzbekistan Academy of Sciences) and Y. Hashidoko (Hokkaido University) for advice on this study.

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Author notes

  1. These authors contributed equally: Xiaoyu Liu, Haruna Matsumoto, Mengcen Wang.

Authors and Affiliations

  1. State Key Laboratory of Rice Biology, and Ministry of Agricultural and Rural Affairs Laboratory of Molecular Biology of Crop Pathogens and Insects, Zhejiang University, Hangzhou, China

    Xiaoyu Liu, Haruna Matsumoto, Tianxing Lv, Chengfang Zhan, Hongda Fang, Qianqian Pan, Haorong Xu, Xiaoyan Fan, Tianyi Chu, Kun Qiao, Qiangwei Wang & Mengcen Wang

  2. Key Laboratory of Biology of Crop Pathogens and Insects of Zhejiang Province, Institute of Pesticide and Environmental Toxicology, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China

    Xiaoyu Liu, Haruna Matsumoto, Tianxing Lv, Chengfang Zhan, Hongda Fang, Qianqian Pan, Haorong Xu, Xiaoyan Fan, Tianyi Chu, Kun Qiao, Qiangwei Wang & Mengcen Wang

  3. Australian Research Council Centre of Excellence in Plant Energy Biology, The University of Western Australia, Perth, Western Australia, Australia

    Xiaoyu Liu

  4. CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China

    Xiaoyan Fan

  5. State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China

    Sunlu Chen

  6. China National Rice Research Institute, Hangzhou, China

    Youning Ma

  7. Department of Neurobiology, School of Medicine, Zhejiang University, Hangzhou, China

    Li Sun

  8. Global Education Program for AgriScience Frontiers, Graduate School of Agriculture, Hokkaido University, Sapporo, Japan

    Mengcen Wang

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Contributions

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

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Correspondence to Mengcen Wang.

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Extended data

Extended Data Fig. 1 Rhizosphere microbial diversity indices of diseased plants and disease-suppressive plants.

a,b, Chao1 index and Simpson index of rhizosphere bacterial community in diseased plants (DPs) and disease-suppressive plants (DSPs). c,d, Chao1 index and Simpson index of rhizosphere fungal community in DPs and DSPs. No significant difference was observed between DPs and DSPs. Values are means ± SD (shown as error bars; n = 3 biological replicates, and each included a mixture of 10 rhizosphere samples), and ‘ns’ shown on the top of the paired columns indicates no significant difference (P > 0.05, unpaired Student’s t test, two-tailed).

Source data

Extended Data Fig. 2 Rhizosphere microbial community structures of diseased plants and disease-suppressive plants.

Bacterial (a,b) and fungal (c,d) community structures were analysed in the rhizosphere of diseased plants (DPs) and disease-suppressive plants (DSPs), respectively (n = 3 biological replicates, and each included a mixture of 10 rhizosphere samples). The microbial community was visualized at phylum (a,c) and genus (b,d) level. The taxonomy was assessed at genus level whenever possible; when taxonomy was only assignable at family level, ‘f’ was added in front of the Latin name.

Extended Data Fig. 3 Composition of microbial community in the panicles of diseased plants and disease-suppressive plants.

Bacterial (a,b) and fungal (c,d) community structures were analysed in the panicles of diseased plants (DPs) and disease-suppressive plants (DSPs), respectively (n = 3 biological replicates, and each included a mixture of 10 rhizosphere samples). The microbial community was visualized at phylum (a,c) and genus (b,d) level. The taxonomy was assessed at genus level whenever possible; when taxonomy was only assignable at family level, ‘f’ was added in front of the Latin name.

Extended Data Fig. 4 The control efficacy leucine and tebuconazole on U. virens-caused RFS in the field trials.

The conventional fungicide tebuconazole (430 g/L SC) and leucine (1% AS) developed in this study were applied at the dose of 96.75 g/hm2 and 120 g/hm2, respectively. Asterisks indicate 50% reduction of the dose. In 2019, the field trial was done in Jiaxing (a) and Hangzhou (b); in 2020, the field trial was done in Shaoxing (c) and Jinhua (d); in 2021, the field trial was done in Taizhou (e). All of these regions (f) are representative rice production regions in Southeast China. Different letters with error bars indicate a significant difference according to one-way analysis of variance (ANOVA) with Tukey’s HSD test (P < 0.01). Values are means ± SD (shown as error bars; n = 5 survey points; each point included 15 panicles).

Source data

Extended Data Fig. 5 Construction and identification of the UvLAO2 mutation in U. virens.

a, The gene knock-out strategy of UvLAO2 in U. virens Genome. PCR primers used for verification were marked with small arrows. Hph, Hygromycin B phosphotransferase gene. Scale bar = 500 bp. b,c, Identification of UvLAO2 mutant (ΔUvlao2) by PCR assays using two primer pairs (including LAO2-F/R and LAO2up + hph-F/R). The LAO2-F/R-amplified product were detected in the genome of wild type (WT) of U. virens, but it was absent in ΔUvlao2 (b); The LAO2up + hph-F/R-amplified product was not detected in the genome of WT of U. virens, but detectable in ΔUvlao2 (c). d, DNA mutation of UvLAO2 gene in ΔUvlao2. The same sequence and different sequences are displayed in light blue and white, respectively.

Extended Data Fig. 6 Effect of amino acids on accumulation of H2O2 and pathogenicity of U. virens.

BCAAs including leucine (Leu), valine (Val) and isoleucine (Ile), and non-BCAAs including Alanine (Ala), Phenylalanine (Phe), Tyrosine (Tyr), Methionine (Met), Aspartic acid (Asp) and Tryptophan (Trp) were used to test their effects on H2O2 accumulation in U. virens (a). In addition, formation of false smut balls in the panicles infected with U. virens was observed for comparison of disease suppressive effects of these amino acids (b). Values are means ± SD (shown as error bars; n = 5 batches of media or 5 panicles). Different letters with error bars indicate a significant difference according to one-way analysis of variance (ANOVA) with Tukey’s HSD test (P < 0.05).

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Liu, X., Matsumoto, H., Lv, T. et al. Phyllosphere microbiome induces host metabolic defence against rice false-smut disease. Nat Microbiol 8, 1419–1433 (2023). https://doi.org/10.1038/s41564-023-01379-x

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