This article has been updated


Tomato variety Hawaii 7996 is resistant to the soil-borne pathogen Ralstonia solanacearum, whereas the Moneymaker variety is susceptible to the pathogen. To evaluate whether plant-associated microorganisms have a role in disease resistance, we analyzed the rhizosphere microbiomes of both varieties in a mesocosm experiment. Microbiome structures differed between the two cultivars. Transplantation of rhizosphere microbiota from resistant plants suppressed disease symptoms in susceptible plants. Comparative analyses of rhizosphere metagenomes from resistant and susceptible plants enabled the identification and assembly of a flavobacterial genome that was far more abundant in the resistant plant rhizosphere microbiome than in that of the susceptible plant. We cultivated this flavobacterium, named TRM1, and found that it could suppress R. solanacearum-disease development in a susceptible plant in pot experiments. Our findings reveal a role for native microbiota in protecting plants from microbial pathogens, and our approach charts a path toward the development of probiotics to ameliorate plant diseases.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Change history

  • 23 October 2018

    In the version of this article initially published online, the citations to Supplementary Figures 12a and 12b were interchanged in section "TRM1 and disease resistance" and the last sentence of Results referred to the rhizosphere of Hawaii 7996; it should have referred to that of Moneymaker pretreated with TRM1-10. The error has been corrected in the print, PDF and HTML versions of this article.


Primary accessions


Gene Expression Omnibus


  1. 1.

    , & Pivoting the plant immune system from dissection to deployment. Science 341, 746–751 (2013).

  2. 2.

    & The plant immune system. Nature 444, 323–329 (2006).

  3. 3.

    , , & Interplay between innate immunity and the plant microbiota. Annu. Rev. Phytopathol. 55, 565–589 (2017).

  4. 4.

    Plant Pathology (Elsevier Academic Press, Burlington, Massachusetts, USA, 2005).

  5. 5.

    et al. Induced systemic resistance by beneficial microbes. Annu. Rev. Phytopathol. 52, 347–375 (2014).

  6. 6.

    et al. Salicylic acid modulates colonization of the root microbiome by specific bacterial taxa. Science 349, 860–864 (2015).

  7. 7.

    , , & Plant Physiology and Development 761 (Sinauer Associates, Sunderland, Massachusetts, USA, 2015).

  8. 8.

    et al. Microbiota and host nutrition across plant and animal kingdoms. Cell Host Microbe 17, 603–616 (2015).

  9. 9.

    , & Ver Loren van Themaat, E. & Schulze-Lefert, P. Structure and functions of the bacterial microbiota of plants. Annu. Rev. Plant Biol. 64, 807–838 (2013).

  10. 10.

    , , The rhizosphere microbiome: significance of plant beneficial, plant pathogenic, and human pathogenic microorganisms. FEMS Microbiol. Rev. 37, 634–663 (2013).

  11. 11.

    , , & Going back to the roots: the microbial ecology of the rhizosphere. Nat. Rev. Microbiol. 11, 789–799 (2013).

  12. 12.

    , , & The plant microbiome explored: implications for experimental botany. J. Exp. Bot. 67, 995–1002 (2016).

  13. 13.

    et al. Root microbiota drive direct integration of phosphate stress and immunity. Nature 543, 513–518 (2017).

  14. 14.

    et al. Defining the core Arabidopsis thaliana root microbiome. Nature 488, 86–90 (2012).

  15. 15.

    et al. Revealing structure and assembly cues for Arabidopsis root-inhabiting bacterial microbiota. Nature 488, 91–95 (2012).

  16. 16.

    et al. Structure and function of the bacterial root microbiota in wild and domesticated barley. Cell Host Microbe 17, 392–403 (2015).

  17. 17.

    , , & The plant microbiota: systems-level insights and perspectives. Annu. Rev. Genet. 50, 211–234 (2016).

  18. 18.

    et al. Research priorities for harnessing plant microbiomes in sustainable agriculture. PLoS Biol. 15, e2001793 (2017).

  19. 19.

    , , & Communication in the Phytobiome. Cell 169, 587–596 (2017).

  20. 20.

    et al. Large-scale replicated field study of maize rhizosphere identifies heritable microbes. Proc. Natl. Acad. Sci. USA 115, 7368–7373 (2018).

  21. 21.

    Tomato Genome Consortium. The tomato genome sequence provides insights into fleshy fruit evolution. Nature 485, 635–641 (2012).

  22. 22.

    Biology and epidemiology of bacterial wilt caused by pseudomonas solanacearum. Annu. Rev. Phytopathol. 29, 65–87 (1991).

  23. 23.

    et al. Top 10 plant pathogenic bacteria in molecular plant pathology. Mol. Plant Pathol. 13, 614–629 (2012).

  24. 24.

    Bacterial wilt disease and the Ralstonia solanacearum species complex 9–28 (APS Press, St. Paul, Minnesota, USA, 2005).

  25. 25.

    Breeding for resistances to Ralstonia solanacearum. Front. Plant Sci. 5, 715 (2014).

  26. 26.

    et al. Resistance of tomato line Hawaii7996 to Ralstonia solanacearum Pss4 in Taiwan is controlled mainly by a major strain-specific locus. Mol. Plant Microbe Interact. 13, 6–13 (2000).

  27. 27.

    et al. Loss of glutamate dehydrogenase in Ralstonia solanacearum alters dehydrogenase activity, extracellular polysaccharide production and bacterial virulence. Physiol. Mol. Plant Pathol. 90, 57–64 (2015).

  28. 28.

    , , & Expanded microbial genome coverage and improved protein family annotation in the COG database. Nucleic Acids Res. 43, D261–D269 (2015).

  29. 29.

    et al. Root exudate metabolites drive plant-soil feedbacks on growth and defense by shaping the rhizosphere microbiota. Nat. Commun. 9, 2738 (2018).

  30. 30.

    et al. Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes. Nat. Biotechnol. 31, 533–538 (2013).

  31. 31.

    et al. Flavobacterium daejeonense sp. nov. and Flavobacterium suncheonense sp. nov., isolated from greenhouse soils in Korea. Int. J. Syst. Evol. Microbiol. 56, 1645–1649 (2006).

  32. 32.

    , & Novel strains isolated from a coastal aquifer suggest a predatory role for flavobacteria. FEMS Microbiol. Ecol. 73, 254–270 (2010).

  33. 33.

    , & The nexus between growth and defense signaling: auxin and cytokinin modulate plant immune response pathways. J. Exp. Bot. 66, 4885–4896 (2015).

  34. 34.

    & New insights into the role of siderophores as triggers of plant immunity: what can we learn from animals? J. Exp. Bot. 66, 3001–3010 (2015).

  35. 35.

    et al. Pseudomonas putida KT2440 causes induced systemic resistance and changes in Arabidopsis root exudation. Environ. Microbiol. Rep. 2, 381–388 (2010).

  36. 36.

    , & Root inoculation with Pseudomonas putida KT2440 induces transcriptional and metabolic changes and systemic resistance in maize plants. Front. Plant Sci. 5, 719 (2015).

  37. 37.

    et al. Identification of major QTLs associated with stable resistance of tomato cultivar 'Hawaii 7996' to Ralstonia solanacearum. Euphytica 190, 241–252 (2013).

  38. 38.

    et al. Deciphering the rhizosphere microbiome for disease-suppressive bacteria. Science 332, 1097–1100 (2011).

  39. 39.

    , , & Microbial populations responsible for specific soil suppressiveness to plant pathogens. Annu. Rev. Phytopathol. 40, 309–348 (2002).

  40. 40.

    et al. Microbial and biochemical basis of a Fusarium wilt-suppressive soil. ISME J. 10, 119–129 (2016).

  41. 41.

    , & Recovering complete and draft population genomes from metagenome datasets. Microbiome 4, 8 (2016).

  42. 42.

    , , & Master recyclers: features and functions of bacteria associated with phytoplankton blooms. Nat. Rev. Microbiol. 12, 686–698 (2014).

  43. 43.

    , & Integrated regulation of the type III secretion system and other virulence determinants in Ralstonia solanacearum. PLoS Pathog. 2, e82 (2006).

  44. 44.

    & Pathogenomics of the Ralstonia solanacearum species complex. Annu. Rev. Phytopathol. 50, 67–89 (2012).

  45. 45.

    , , & Comparative transcriptome analysis reveals cool virulence factors of Ralstonia solanacearum race 3 biovar 2. PLoS One 10, e0139090 (2015).

  46. 46.

    et al. Trophic network architecture of root-associated bacterial communities determines pathogen invasion and plant health. Nat. Commun. 6, 8413 (2015).

  47. 47.

    et al. Functional overlap of the Arabidopsis leaf and root microbiota. Nature 528, 364–369 (2015).

  48. 48.

    et al. Genome sequence of the polymyxin-producing plant-probiotic rhizobacterium Paenibacillus polymyxa E681. J. Bacteriol. 192, 6103–6104 (2010).

  49. 49.

    & Host biology in light of the microbiome: ten principles of holobionts and hologenomes. PLoS Biol. 13, e1002226 (2015).

  50. 50.

    The hologenome: A new view of evolution. New Sci. 2899, 30–34 (2013).

  51. 51.

    et al. Quantitative trait loci determining resistance to bacterial wilt in tomato cultivar Hawaii 7996. Mol. Plant Microbe Interact. 9, 826–836 (1996).

  52. 52.

    Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012).

  53. 53.

    , , & Using the RDP classifier to predict taxonomic novelty and reduce the search space for finding novel organisms. PLoS One 7, e32491 (2012).

  54. 54.

    , , & Statistical evaluation of methods for identification of differentially abundant genes in comparative metagenomics. BMC Genomics 17, 78 (2016).

  55. 55.

    et al. Gut microbiota modulated by probiotics and Garcinia cambogia extract correlate with weight gain and adipocyte sizes in high fat-fed mice. Sci. Rep. 6, 33566 (2016).

  56. 56.

    , & edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010).

  57. 57.

    , & Ab initio gene identification in metagenomic sequences. Nucleic Acids Res. 38, e132 (2010).

  58. 58.

    & Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22, 1658–1659 (2006).

  59. 59.

    et al. The DOE-JGI standard operating procedure for the annotations of microbial genomes. Stand. Genomic Sci. 1, 63–67 (2009).

  60. 60.

    et al. Induction of the viable but nonculturable state of Ralstonia solanacearum by low temperature in the soil microcosm and its resuscitation by catalase. PLoS One 9, e109792 (2014).

  61. 61.

    , & Cloning of the egl gene of Pseudomonas solanacearum and analysis of its role in phytopathogenicity. J. Bacteriol. 170, 1445–1451 (1988).

  62. 62.

    & A new medium for the enumeration and subculture of bacteria from potable water. Appl. Environ. Microbiol. 49, 1–7 (1985).

  63. 63.

    et al. GeneFisher-P: variations of GeneFisher as processes in Bio-jETI. BMC Bioinformatics 9(Suppl. 4), S13 (2008).

  64. 64.

    et al. Genomic insights to SAR86, an abundant and uncultivated marine bacterial lineage. ISME J. 6, 1186–1199 (2012).

  65. 65.

    et al. Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea. Nat. Biotechnol. 35, 725–731 (2017).

  66. 66.

    , , , & CAZymes Analysis Toolkit (CAT): web service for searching and analyzing carbohydrate-active enzymes in a newly sequenced organism using CAZy database. Glycobiology 20, 1574–1584 (2010).

  67. 67.

    , , & The transporter classification database. Nucleic Acids Res. 42, D251–D258 (2014).

  68. 68.

    , & Laboratory guide for identification of plant Pathogenic bacteria (American Phytopathological Society Press, St. Paul, USA, 2001).

  69. 69.

    et al. A novel method for development of species and strain specific DNA probes and PCR primers for identifying Burkholderia solanacearum (formerly Pseudomonas solanacearum). Asia Pac. J. Mol. Biol. Biotechnol. 5, 19–30 (1997).

Download references


We would like to thank members of the laboratories of J.F.K. and S.-W.L., including B.K. Kim, K.Y. Baek, T.-H. Kang, S. Kim, H.G. Lee, S.Y. Lee, G.J. Son, S. Yoo and H. Yu, as well as KRIBB-KOBIC and NABIC, for technical support, and Y.-S. Bahn, D. Choi, S.-Y. Kwon, I. Lee, W.-J. Lee and H.-S. Pai for helpful comments and suggestions. This study was financially supported by the Strategic Initiative for Microbiomes in Agriculture and Food (914001-4 to J.F.K. and 914006-4 to J.Y.S.), the Cooperative Research Program for Agricultural Science & Technology Development (PJ01093901 to S.-W.L.), the National Research Foundation (NRF-2014M3C9A33068822 and NRF-2011-0017670 to J.F.K.), and the Next-Generation BioGreen 21 Program (PJ008201 to S.-W.L.) of the Republic of Korea. Publication was supported in part by the Brain Korea 21 PLUS program, and M.-J.K., S.-K.K. and J.L. are fellowship awardees of the program.

Author information

Author notes

    • Minseok Seo
    •  & Edward M Rubin

    Present addresses: Channing Division of Network Medicine, Harvard Medical School and Brigham and Women's Hospital, Boston, Massachusetts, USA (M.S.) and Metabiota Inc., San Francisco, California, USA (E.M.R.).

    • Min-Jung Kwak
    • , Hyun Gi Kong
    • , Kihyuck Choi
    • , Soon-Kyeong Kwon
    •  & Ju Yeon Song

    These authors contributed equally to this work.


  1. Department of Systems Biology, Division of Life Sciences, and Institute for Life Science and Biotechnology, Yonsei University, Seoul, Republic of Korea.

    • Min-Jung Kwak
    • , Soon-Kyeong Kwon
    • , Ju Yeon Song
    • , Jidam Lee
    • , Hyein Park
    • , Myeong Min Lee
    •  & Jihyun F Kim
  2. Department of Applied Biology, Dong-A University, Busan, Republic of Korea.

    • Hyun Gi Kong
    • , Kihyuck Choi
    • , Pyeong An Lee
    • , Soo Yeon Choi
    • , Hyoung Ju Lee
    • , Eun Joo Jung
    • , Nazish Roy
    •  & Seon-Woo Lee
  3. C&K Genomics, Seoul, Republic of Korea.

    • Minseok Seo
    •  & Heebal Kim
  4. Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, Republic of Korea.

    • Heebal Kim
  5. Department of Energy Joint Genome Institute (DOE JGI) and Lawrence Berkeley National Laboratory, Berkeley, California, USA.

    • Edward M Rubin
  6. Strategic Initiative for Microbiomes in Agriculture and Food (iMAF), Yonsei University, Seoul, Republic of Korea.

    • Jihyun F Kim


  1. Search for Min-Jung Kwak in:

  2. Search for Hyun Gi Kong in:

  3. Search for Kihyuck Choi in:

  4. Search for Soon-Kyeong Kwon in:

  5. Search for Ju Yeon Song in:

  6. Search for Jidam Lee in:

  7. Search for Pyeong An Lee in:

  8. Search for Soo Yeon Choi in:

  9. Search for Minseok Seo in:

  10. Search for Hyoung Ju Lee in:

  11. Search for Eun Joo Jung in:

  12. Search for Hyein Park in:

  13. Search for Nazish Roy in:

  14. Search for Heebal Kim in:

  15. Search for Myeong Min Lee in:

  16. Search for Edward M Rubin in:

  17. Search for Seon-Woo Lee in:

  18. Search for Jihyun F Kim in:


J.F.K. and S.-W.L. conceived, organized and supervised the project. J.F.K., S.-W.L., M.M.L. and E.M.R. interpreted the results and prepared the manuscript. People in the laboratory of S.-W.L. performed the plant experiments; those in J.F.K.'s lab. analyzed the metagenomic data. M.-J.K. worked on the metagenome analysis, reconstructed TRG1, and drafted the microbiome results. H.J.L. contributed to setting up the plant experiment. H.G.K. and K.C. extracted the metagenomic DNA and analyzed the pyrosequencing data. J.Y.S. carried out the comparative analysis on field and pot experiments. M.S. and H.K. performed the statistical analysis for community structures. S.Y.C. and E.J.J. performed the transplant experiment as well as the isolation and phenotypic characterization of flavobacteria. K.C. and P.A.L. tested the influence of root exudates on bacterial growth. J.Y.S. annotated TRG1. M.-J.K., S.-K.K., and J.L. analyzed the genome information. J.L. and M.-J.K. isolated and characterized TRM1. P.A.L., J.L., and K.C. tested its effect as well as those of other flavobacteria on disease progress. Finally, S.-K.K., P.A.L., and N.R. performed the qPCR analysis. K.C., P.A.L., H.P., and N.R. enumerated cultured bacteria. J.F.K. composed the main text. J.F.K., S.-W.L., and M.-J.K. edited the manuscript. All of the authors read and approved the final version of the manuscript before submission.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Seon-Woo Lee or Jihyun F Kim.

Integrated supplementary information

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–13

  2. 2.

    Life Sciences Reporting Summary

  3. 3.

    Supplementary Tables

    Supplementary Tables 1–18

About this article

Publication history





Further reading