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Changes in Bacterial and Fungal Microbiomes Associated with Tomatoes of Healthy and Infected by Fusarium oxysporum f. sp. lycopersici

  • Soil Microbiology
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Abstract

Fusarium wilt of tomato caused by the pathogen Fusarium oxysporum f. sp. lycopersici (Fol) is one of the most devastating soilborne diseases of tomato. To evaluate whether microbial community composition associated with Fol-infected tomato is different from healthy tomato, we analyzed the tomato-associated microbes in both healthy and Fol-infected tomato plants at both the taxonomic and functional levels; both bacterial and fungal communities have been characterized from bulk soil, rhizosphere, rhizoplane, and endosphere of tomatoes using metabarcoding and metagenomics approaches. The microbial community (bacteria and fungi) composition of healthy tomato was significantly different from that of diseased tomato, despite similar soil physicochemical characteristics. Both fungal and bacterial diversities were significantly higher in the tomato plants that remained healthy than in those that became diseased; microbial diversities were also negatively correlated with the concentration of Fol pathogen. Network analysis revealed the microbial community of healthy tomato formed a larger and more complex network than that of diseased tomato, probably providing a more stable community beneficial to plant health. Our findings also suggested that healthy tomato contained significantly greater microbial consortia, including some well-known biocontrol agents (BCAs), and enriched more functional genes than diseased tomato. The microbial taxa enriched in healthy tomato plants are recognized as potential suppressors of Fol pathogen invasion.

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References

  1. Srinivas C, Devi DN, Murthy KN et al (2019) Fusarium oxysporum f. sp. lycopersici causal agent of vascular wilt disease of tomato: biology to diversity-a review. Saudi J Boil Sci 26:1315–1324. https://doi.org/10.1016/j.sjbs.2019.06.002

    Article  CAS  Google Scholar 

  2. Gordon TR (2017) Fusarium oxysporum and the Fusarium wilt syndrome. Annu Rev Phytopathol 55:23–39. https://doi.org/10.1146/annurev-phyto-080615-095919

    Article  CAS  PubMed  Google Scholar 

  3. Duffy B, Défago G (1999) Macro-and microelement fertilizers influence the severity of Fusarium crown and root rot of tomato in a soilless production system. HortScience 34(2):287–291. https://doi.org/10.21273/HORTSCI.34.2.287

    Article  CAS  Google Scholar 

  4. Gareau BJ (2010) A critical review of the successful CFC phase-out versus the delayed methyl bromide phase-out in the Montreal Protocol. Int Environ Agreements 10:209–231. https://doi.org/10.1007/s10784-010-9120-z

    Article  Google Scholar 

  5. Martin FN (2003) Development of alternative strategies for management of soilborne pathogens currently controlled with methyl bromide. Annu Rev Phytopathol 41(1):325–350. https://doi.org/10.1146/annurev.phyto.41.052002.095514

    Article  CAS  PubMed  Google Scholar 

  6. Giotis C, Markelou E, Theodoropoulou A, Toufexi E, Hodson R, Shotton P, Shiel R, Cooper J, Leifert C (2009) Effect of soil amendments and biological control agents (BCAs) on soil-borne root diseases caused by Pyrenochaeta lycopersici and Verticillium alboatrum in organic greenhouse tomato production systems. Eur J Plant Pathol 123(4):387–400. https://doi.org/10.1007/s10658-008-9376-0

    Article  Google Scholar 

  7. Toju H, Peay KG, Yamamichi M, Narisawa K, Hiruma K, Naito K, Fukuda S, Ushio M, Nakaoka S, Onoda Y, Yoshida K, Schlaeppi K, Bai Y, Sugiura R, Ichihashi Y, Minamisawa K, Kiers ET (2018) Core microbiomes for sustainable agroecosystems. Nat Plants 4(9):733–733. https://doi.org/10.1038/s41477-018-0245-3

    Article  PubMed  Google Scholar 

  8. Van Der H, Bardgett MG, RD and Van Straalen NM. (2008) The unseen majority: soil microbes as drivers of plant diversity and productivity in terrestrial ecosystems. Ecol Lett 11:296–310. https://doi.org/10.1111/j.1461-0248.2007.01139.x

    Article  Google Scholar 

  9. Nuzzo A, Satpute A, Albrecht U, Strauss SL (2020) Impact of soil microbial amendments on tomato rhizosphere microbiome and plant growth in field soil. Microb Ecol. https://doi.org/10.1007/s00248-020-01497-7

  10. Mendes R, Kruijt M, de Bruijn I, Dekkers E, van der Voort M, Schneider JHM, Piceno YM, DeSantis TZ, Andersen GL, Bakker PAHM, Raaijmakers JM (2011) Deciphering the rhizosphere microbiome for disease-suppressive bacteria. Science 332(6033):1097–1100. https://doi.org/10.1126/science.1203980

    Article  CAS  PubMed  Google Scholar 

  11. Vandenkoornhuyse P, Quaiser A, Duhamel M, Van L, Dufresne A (2015) The importance of the microbiome of the plant holobiont. New Phytol 206:1196–1206. https://doi.org/10.1111/nph.13312

    Article  PubMed  Google Scholar 

  12. Hu J, Wei Z, Friman VP, Gu SH, Wang XF, Eisenhauer N, Yang TJ, Ma J, Shen QR, Xu YC, Jousset A (2016) Probiotic diversity enhances rhizosphere microbiome function and plant disease suppression. Mbio 7(6). https://doi.org/10.1128/mBio.01790-16

  13. Kwak M, Kong H, Choi K et al (2018) Rhizosphere microbiome structure alters to enable wilt resistance in tomato. Nat Biotechnol 36:1100–1109. https://doi.org/10.1038/nbt.4232

    Article  CAS  Google Scholar 

  14. Carrión VJ, Perez-Jaramillo J, Cordovez V, Tracanna V, de Hollander M, Ruiz-Buck D, Mendes LW, van Ijcken WFJ, Gomez-Exposito R, Elsayed SS, Mohanraju P, Arifah A, van der Oost J, Paulson JN, Mendes R, van Wezel GP, Medema MH, Raaijmakers JM (2019) Pathogen-induced activation of disease-suppressive functions in the endophytic root microbiome. Science 366(6465):606–612. https://doi.org/10.1126/science.aaw9285

    Article  CAS  PubMed  Google Scholar 

  15. Chialva M, Zhou Y, Spadaro D, Bonfante P (2018) Not only priming: soil microbiota may protect tomato from root pathogens. Plant Signal Behav 13(8):1–9. https://doi.org/10.1080/15592324.2018.1464855

    Article  CAS  Google Scholar 

  16. Finkel OM, Castrillo G, Paredes SH, González IS, Dangl JL (2017) Understanding and exploiting plant beneficial microbes. Curr Opin Plant Biol 38:155–163. https://doi.org/10.1016/j.pbi.2017.04.018

    Article  PubMed  PubMed Central  Google Scholar 

  17. Larkin RP, Fravel DR (1998) Efficacy of various fungal and bacterial biocontrol organisms for control of Fusarium wilt of tomato. Plant Dis 82(9):1022–1028. https://doi.org/10.1094/PDIS.1998.82.9.1022

    Article  PubMed  Google Scholar 

  18. Fravel DR (2005) Commercialization and implementation of biocontrol. Annu Rev Phytopathol 43:337–359. https://doi.org/10.1146/annurev.phyto.43.032904.092924

    Article  CAS  PubMed  Google Scholar 

  19. Ousley MA, Lynch JM, Whipps JM (1993) Effect of Trichoderma on plant growth: a balance between inhibition and growth promotion. Microb Ecol 26:277–285. https://doi.org/10.1007/BF00176959

    Article  CAS  PubMed  Google Scholar 

  20. Zhou D, Feng H, Schuelke T, de Santiago A, Zhang Q, Zhang J, Luo C, Wei L (2019) Rhizosphere microbiomes from root knot nematode non-infested plants suppress nematode infection. Microb Ecol 78:470–481. https://doi.org/10.1007/s00248-019-01319-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Niu B, Paulson JN, Zheng X, Kolter R (2017) Simplified and representative bacterial community of maize roots. PNAS 114(12):E2450–E2459. https://doi.org/10.1073/pnas.1616148114

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Coyte KZ, Schluter J, Foster KR (2015) The ecology of the microbiome: networks, competition, and stability. Science 350(6261):663–666. https://doi.org/10.1126/science.aad2602

    Article  CAS  PubMed  Google Scholar 

  23. Gómez Expósito R, de Bruijn I, Postma J, Raaijmakers JM (2017) Current insights into the role of rhizosphere bacteria in disease suppressive soils. Front Microbiol 8(2529). https://doi.org/10.3389/fmicb.2017.02529

  24. Wei Z, Gu Y, Friman VP, Kowalchuk GA, Xu Y, Shen Q, Jousset A (2019) Initial soil microbiome composition and functioning predetermine future plant health. Sci Adv 5(9):eaaw0759. https://doi.org/10.1126/sciadv.aaw0759

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Martínez-Medina A, Fernandez I, Lok GB, Pozo MJ, Pieterse CMJ, Van Wees SCM (2017) Shifting from priming of salicylic acid-to jasmonic acid-regulated defences by Trichoderma protects tomato against the root knot nematode Meloidogyne incognita. New Phytol 213:1363–1377. https://doi.org/10.1111/nph.14251

    Article  CAS  PubMed  Google Scholar 

  26. Edwards J, Johnson C, Santos-Medellin C et al (2015) Structure, variation, and assembly of the root-associated microbiomes of rice. PNAS 112(8):E911–E920. https://doi.org/10.1073/pnas.1414592112

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Xu N, Tan G, Wang H, Gai X (2016) Effect of biochar additions to soil on nitrogen leaching, microbial biomass and bacterial community structure. Eur J Soil Biol 74:1–8. https://doi.org/10.1016/j.ejsobi.2016.02.004

    Article  CAS  Google Scholar 

  28. Adams R, Miletto M, Taylor J et al (2013) Dispersal in microbes: fungi in indoor air are dominated by outdoor air and show dispersal limitation at short distances. ISME J 7:1262–1273. https://doi.org/10.1038/ismej.2013.28

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Inami K, Yoshioka C, Hirano Y, Kawabe M, Tsushima S, Teraoka T, Arie T (2010) Real-time PCR for differential determination of the tomato wilt fungus, Fusarium oxysporum f. sp. lycopersici, and its races. J Gen Plant Pathol 76:116–121. https://doi.org/10.1007/s10327-010-0224-7

    Article  CAS  Google Scholar 

  30. Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30(15):2114–2120. https://doi.org/10.1093/bioinformatics/btu170

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Langmead B, Salzberg S (2012) Fast gapped-read alignment with Bowtie 2. Nat Methods 9:357–359. https://doi.org/10.1038/nmeth.1923

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Segata N, Waldron L, Ballarini A, Narasimhan V, Jousson O, Huttenhower C (2012) Metagenomic microbial community profiling using unique clade-specific marker genes. Nat Methods 9:811–814. https://doi.org/10.1038/nmeth.2066

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Abubucker S, Segata N, Goll J, Schubert AM, Izard J, Cantarel BL, Rodriguez-Mueller B, Zucker J, Thiagarajan M, Henrissat B, White O, Kelley ST, Methé B, Schloss PD, Gevers D, Mitreva M, Huttenhower C (2012) Metabolic reconstruction for metagenomic data and its application to the human microbiome. PLoS Comput Biol 8(6):e1002358. https://doi.org/10.1371/journal.pcbi.1002358

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Parks DH, Tyson GW, Hugenholtz P, Beiko RG (2014) STAMP: statistical analysis of taxonomic and functional profiles. Bioinformatics 30(21):3123–3124. https://doi.org/10.1093/bioinformatics/btu494

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, Huttenhower C (2011) Metagenomic biomarker discovery and explanation. Genome Biol 12:R60. https://doi.org/10.1186/gb-2011-12-6-r60

    Article  PubMed  PubMed Central  Google Scholar 

  36. Edgar R (2013) UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat Methods 10:996–998. https://doi.org/10.1038/nmeth.2604

    Article  CAS  PubMed  Google Scholar 

  37. Rognes T, Flouri T, Nichols B, Quince C, Mahé F (2016) VSEARCH: a versatile open source tool for metagenomics. PeerJ 4:e2584. https://doi.org/10.7717/peerj.2584

    Article  PubMed  PubMed Central  Google Scholar 

  38. Nilsson RH, Tedersoo L, Ryberg M, Kristiansson E, Hartmann M, Unterseher M, Porter TM, Bengtsson-Palme J, Walker DM, de Sousa F, Gamper HA, Larsson E, Larsson KH, Kõljalg U, Edgar RC, Abarenkov K (2015) A comprehensive, automatically updated fungal ITS sequence dataset for reference-based chimera control in environmental sequencing efforts. Microbes Environ 30(2):145–150. https://doi.org/10.1264/jsme2.ME14121

    Article  PubMed  PubMed Central  Google Scholar 

  39. Deshpande V, Wang Q, Greenfield P, Charleston M, Porras-Alfaro A, Kuske CR, Cole JR, Midgley DJ, Tran-Dinh N (2016) Fungal identification using a Bayesian classifier and the Warcup training set of internal transcribed spacer sequences. Mycologia 108(1):1–5. https://doi.org/10.3852/14-293

    Article  PubMed  Google Scholar 

  40. Oksanen AJ, Blanchet FG, Friendly M, et al (2016) Vegan: community ecology package. https://github.com/vegandevs/vegan

  41. Lozupone C, Knight R (2005) UniFrac: a new phylogenetic method for comparing microbial communities. Appl Environ Microbiol 71(12):8228–8235. https://doi.org/10.1128/AEM.71.12.8228-8235.2005

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Robinson MD, McCarthy DJ, Smyth GK (2010) edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26(1):139–140. https://doi.org/10.1093/bioinformatics/btp616

    Article  CAS  PubMed  Google Scholar 

  43. Wickham H (2009) ggplot2: elegant graphics for data analysis. Springer, New York

    Book  Google Scholar 

  44. Csardi G, Nepusz T (2006) The igraph software package for complex network research. InterJournal Complex Systems 1695

  45. Clauset A, Newman ME, Moore C (2004) Finding community structure in very large networks. Phys Rev E 70:066111. https://doi.org/10.1103/PhysRevE.70.066111

    Article  CAS  Google Scholar 

  46. Agler MT, Ruhe J, Kroll S, Morhenn C, Kim ST, Weigel D, Kemen EM (2016) Microbial hub taxa link host and abiotic factors to plant microbiome variation. PLoS Biol 14(1):e1002352. https://doi.org/10.1371/journal.pbio.1002352

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Van Der Heijden MG, Hartmann M (2016) Networking in the plant microbiome. PLoS Biol 14(2):e1002378. https://doi.org/10.1371/journal.pbio.1002378

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Kuntal BK, Chandrakar P, Sadhu S, Mande SS (2019) ‘NetShift’: a methodology for understanding ‘driver microbes’ from healthy and disease microbiome datasets. ISME J 13:442–454. https://doi.org/10.1038/s41396-018-0291-x

    Article  PubMed  Google Scholar 

  49. Poudel R, Jumpponen A, Schlatter D et al (2016) Microbiome networks: a systems framework for identifying candidate microbial assemblages for disease management. Phytopathology 106(10):1083–1096. https://doi.org/10.1094/PHYTO-02-16-0058-FI

    Article  CAS  PubMed  Google Scholar 

  50. Santhanam R, Luu VT, Weinhold A, Goldberg J, Oh Y, Baldwin IT (2015) Native root-associated bacteria rescue a plant from a sudden-wilt disease that emerged during continuous cropping. PNAS 112(36):E5013–E5020. https://doi.org/10.1073/pnas.1505765112

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Hirsch PR, Miller AJ, Dennis PG (2013) Do root exudates exert more influence on rhizosphere bacterial community structure than other rhizodeposits? In Molecular Microbial Ecology of the Rhizosphere, F.J. de Bruijn (Ed.). https://doi.org/10.1002/9781118297674.ch22

  52. Reinhold-Hurek B, Bünger W, Burbano CS, Sabale M, Hurek T (2015) Roots shaping their microbiome: global hotspots for microbial activity. Annu Rev Phytopathol 53:403–424. https://doi.org/10.1146/annurev-phyto-082712-102342

    Article  CAS  PubMed  Google Scholar 

  53. Renault D, Laparie M, McCauley SJ, Bonte D (2018) Environmental adaptations, ecological filtering, and dispersal central to insect invasions. Annu Rev Entomol 63:345–368. https://doi.org/10.1146/annurev-ento-020117-043315

    Article  CAS  PubMed  Google Scholar 

  54. Chen Y, Yan F, Chai Y, Liu H, Kolter R, Losick R, Guo JH (2013) Bacillus subtilis and plant biocontrol. Environ Microbiol 15:848–864. https://doi.org/10.1111/j.1462-2920.2012.02860.x

    Article  PubMed  Google Scholar 

  55. Rahman A, Sharifah FS, Singh E, Pieterse CM, Schenk PM (2018) Emerging microbial biocontrol strategies for plant pathogens. Plant Sci 267:102–111. https://doi.org/10.1016/j.plantsci.2017.11.012

    Article  CAS  Google Scholar 

  56. Hu L, Robert CAM, Cadot S, Zhang X, Ye M, Li B, Manzo D, Chervet N, Steinger T, van der Heijden MGA, Schlaeppi K, Erb M (2018) Root exudate metabolites drive plant-soil feedbacks on growth and defense by shaping the rhizosphere microbiota. Nat Commun 9:2738. https://doi.org/10.1038/s41467-018-05122-7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Banerjee S, Kirkby CA, Schmutter D, Bissett A, Kirkegaard JA, Richardson AE (2016) Network analysis reveals functional redundancy and keystone taxa amongst bacterial and fungal communities during organic matter decomposition in an arable soil. Soil Biol Biochem 97:188–198. https://doi.org/10.1016/j.soilbio.2016.03.017

    Article  CAS  Google Scholar 

  58. Banerjee S, Schlaeppi K, Van Der Heijden MGA (2018) Keystone taxa as drivers of microbiome structure and functioning. Nat Rev Microbiol 16:567–576. https://doi.org/10.1038/s41579-018-0024-1

    Article  CAS  PubMed  Google Scholar 

  59. Colombo EM, Kunova A, Pizzatti C, Saracchi M, Cortesi P, Pasquali M (2019) Selection of an endophytic Streptomyces sp. strain DEF09 from wheat roots as a biocontrol agent against Fusarium graminearum. Front Microbiol 10(2356). https://doi.org/10.3389/fmicb.2019.02356

  60. Das K, Prasanna R, Saxena AK (2017) Rhizobia: a potential biocontrol agent for soilborne fungal pathogens. Folia Microbiol 62:425–435. https://doi.org/10.1007/s12223-017-0513-z

    Article  CAS  Google Scholar 

  61. Berendsen RL, Vismans G, Yu K, Song Y, de Jonge R, Burgman WP, Burmølle M, Herschend J, Bakker PAHM, Pieterse CMJ (2018) Disease-induced assemblage of a plant-beneficial bacterial consortium. ISME J 12:1496–1507. https://doi.org/10.1038/s41396-018-0093-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgments

We thank Dr. Wei Liu and Dr. Shenyong Fu (Institute of Microbiology, CAS) for the greenhouse experiments and sample collections, and Dr. Junmin Liang (Institute of Microbiology, CAS) for the editorial support of the manuscript.

Funding

This study was financially supported by NSFC 31725001. X. Zhou received financial support for his studentship (QYZDB-SSW-SMC044). C.K. Tsui acknowledges CAS153211KYSB20160029 for supporting his visit to Chinese Academy of Sciences.

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L. Cai planned and supervised this research; X. Zhou performed the experiments with the assistant of J.T. Wang; X. Zhou conducted the bioinformatic analyses and mainly wrote the manuscript. W.H. Wang and C. K. Tsui contributed to the data analysis and revision of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Lei Cai.

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The authors declare that they have no conflict of interest.

Electronic supplementary material

Fig. S1

Rarefaction curves of tomato bacterial and fungal OTUs. a) Rarefaction curves of tomato bacterial OTUs. b) Rarefaction curves of tomato fungal OTUs. (EPS 835 kb)

Fig. S2

Concentrations of Fol in healthy and diseased tomato plants. a) Comparison of relative abundance of Fol in healthy and diseased tomato groups. b) Comparison of absolute abundance of Fol in healthy and diseased tomato groups. (EPS 757 kb)

Fig. S3

Relative abundance of different bacterial and fungal taxa at the phylum level as revealed by shotgun metagenomics. (EPS 3112 kb)

Fig. S4

Relative abundance of different bacterial and fungal taxa at the genus level as revealed by shotgun metagenomics. (EPS 2394 kb)

Fig. S5

Distinct active functions identified using the LEfSe method. The functional annotations were obtained using HUMAnN2 against the KO database. LDA scores showed significant functional differences between the healthy and diseased groups. Green represents the functions enriched in healthy tomato samples, and the red represents the functions enriched in diseased tomato samples. (EPS 1953 kb)

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Zhou, X., Wang, JT., Wang, WH. et al. Changes in Bacterial and Fungal Microbiomes Associated with Tomatoes of Healthy and Infected by Fusarium oxysporum f. sp. lycopersici. Microb Ecol 81, 1004–1017 (2021). https://doi.org/10.1007/s00248-020-01535-4

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