The relative importance of soil moisture in predicting bacterial wilt disease occurrence

Highlights

• 10-year of CC was a cut-off point in separating soil bacterial community structures.

• soil pH and P were well associated with changes of diversity and community structures.

• N fixation bacteria were increased with successive year, but P, K solubilizing bacteria decreased.

• Monocropped alfalfa simplified the complexity of the cooccurrence networks.

Abstract

Soil-borne plant diseases cause major economic losses globally. This is partly because their epidemiology is difficult to predict in agricultural fields, where multiple environmental factors could determine disease outcomes. Here we used a combination of field sampling and direct experimentation to identify key abiotic and biotic soil properties that can predict the occurrence of bacterial wilt caused by pathogenic Ralstonia solanacearum. By analyzing 139 tomato rhizosphere soils samples isolated from six provinces in China, we first show a clear link between soil properties, pathogen density and plant health. Specifically, disease outcomes were positively associated with soil moisture, bacterial abundance and bacterial community composition. Based on soil properties alone, random forest machine learning algorithm could predict disease outcomes correctly in 75% of cases with soil moisture being the most significant predictor. The importance of soil moisture was validated causally in a controlled greenhouse experiment, where the highest disease incidence was observed at 60% of maximum water holding capacity. Together, our results show that local soil properties can predict disease occurrence across a wider agricultural landscape, and that management of soil moisture could potentially offer a straightforward method for reducing crop losses to R. solanacearum

Graphical abstract

Keywords

Bacterial wilt disease / Soil moisture / Soil physicochemical properties / Rhizosphere bacterial communities / Ralstonia solanacearum / Random forest algorithm

References

[1] Aung, K., Jiang, Y., He, S.Y., 2018. The role of water in plant-microbe interactions. Plant Journal 93, 771–780

[2] Beattie, G.A., 2011. Water relations in the interaction of foliar bacterial pathogens with plants. Annual Review of Phytopathology 49, 533–555

[3] Berg, M., Koskella, B., 2018. Nutrient- and dose-dependent microbiome-mediated protection against a plant pathogen. Current Biology 28, 2487–2492.e3

[4] Breiman, L., and Cutler, A., for Fortran original, Liaw, A., and Wiener, M., for R. port 2018. randomForest: Breiman and Cutler’s Random Forests for Classification and Regression.

[5] Brockett, B.F.T., Prescott, C.E., Grayston, S.J., 2012. Soil moisture is the major factor influencing microbial community structure and enzyme activities across seven biogeoclimatic zones in western Canada. Soil Biology & Biochemistry 44, 9–20

[6] Caporaso, J.G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F.D., Costello, E.K., Fierer, N., Peña, A.G., Goodrich, J.K., Gordon, J.I., Huttley, G.A., Kelley, S.T., Knights, D., Koenig, J.E., Ley, R.E., Lozupone, C.A., McDonald, D., Muegge, B.D., Pirrung, M., Reeder, J., Sevinsky, J.R., Turnbaugh, P.J., Walters, W.A., Widmann, J., Yatsunenko, T., Zaneveld, J., Knight, R., 2010. QIIME allows analysis of high-throughput community sequencing data. Nature Methods 7, 335–336

[7] Cavagnaro, T.R., 2016. Soil moisture legacy effects: Impacts on soil nutrients, plants and mycorrhizal responsiveness. Soil Biology & Biochemistry 95, 173–179

[8] Chairman, J.F.P., Gardner, W.R., Elliott, L.F., eds., 1981. Water potential relations in soil microbiology, SSSA Special Publications. John Wiley & Sons, Ltd.

[9] Chen, M.M., Zhu, Y.G., Su, Y.H., Chen, B.D., Fu, B.J., Marschner, P., 2007. Effects of soil moisture and plant interactions on the soil microbial community structure. European Journal of Soil Biology 43, 31–38

[10] Cheng, Y.T., Zhang, L., He, S.Y., 2019. Plant-microbe interactions facing environmental challenge. Cell Host & Microbe 26, 183–192

[11] Cole, J.R., Wang, Q., Fish, J.A., Chai, B., McGarrell, D.M., Sun, Y., Brown, C.T., Porras-Alfaro, A., Kuske, C.R., Tiedje, J.M., 2014. Ribosomal Database Project: data and tools for high throughput rRNA analysis. Nucleic Acids Research 42, D633–D642

[12] Cuzick, J., 1985. A Wilcoxon-type test for trend. Statistics in Medicine 4, 87–90

[13] Dalsing, B.L., Truchon, A.N., Gonzalez-Orta, E.T., Milling, A.S., Allen, C., 2015. Ralstonia solanacearum uses inorganic nitrogen metabolism for virulence, ATP production, and detoxification in the oxygen-limited host xylem environment. mBio 6, e02471

[14] de Mendiburu, F., 2020. agricolae: Statistical Procedures for Agricultural Research.

[15] Dixon, P., 2003. VEGAN, a package of R functions for community ecology. Journal of Vegetation Science 14, 927–930

[16] Edgar, R.C., 2010. Search and clustering orders of magnitude faster than BLAST. Bioinformatics (Oxford, England) 26, 2460–2461

[17] Fierer, N., Jackson, J.A., Vilgalys, R., Jackson, R.B., 2005. Assessment of soil microbial community structure by use of taxon-specific quantitative PCR assays. Applied and Environmental Microbiology 71, 4117–4120

[18] Genin, S., Denny, T.P., 2012. Pathogenomics of the Ralstonia solanacearum species complex. Annual Review of Phytopathology 50, 67–89

[19] Gu, S., Wei, Z., Shao, Z., Friman, V.P., Cao, K., Yang, T., Kramer, J., Wang, X., Li, M., Mei, X., Xu, Y., Shen, Q., Kümmerli, R., Jousset, A., 2020. Competition for iron drives phytopathogen control by natural rhizosphere microbiomes. Nature Microbiology 5, 1002–1010

[20] Gu, Y., Wang, X., Yang, T., Friman, V.P., Geisen, S., Wei, Z., Xu, Y., Jousset, A., Shen, Q., 2020. Chemical structure predicts the effect of plant-derived low-molecular weight compounds on soil microbiome structure and pathogen suppression. Functional Ecology 34, 2158–2169

[21] Hayward, A.C., 1991. Biology and epidemiology of bacterial wilt caused by Pseudomonas solanacearum. Annual Review of Phytopathology 29, 65–87

[22] Hothorn, T., Bretz, F., Westfall, P., 2008. Simultaneous inference in general parametric models. Biometrical Journal 50, 346–363

[23] Huber, L., Gillespie, T.J., 1992. Modeling leaf wetness in relation to plant disease epidemiology. Annual Review of Phytopathology 30, 553–577

[24] Islam, T., Toyama, K., 2004. Effect of moisture conditions and pre-incubation at low temperature on bacterial wilt of tomato caused by Ralstonia solanacearum. Microbes and Environments 19, 244–247

[25] Janvier, C., Villeneuve, F., Alabouvette, C., Edel-Hermann, V., Mateille, T., Steinberg, C., 2007. Soil health through soil disease suppression: Which strategy from descriptors to indicators? Soil Biology & Biochemistry 39, 1–23

[26] Jiang, G., 2016. Pathogenesis and modelling of infection dynamics in Ralstonia solanacearum (Thesis).

[27] Jiang, G., Wei, Z., Xu, J., Chen, H., Zhang, Y., She, X., Macho, A.P., Ding, W., Liao, B., 2017. Bacterial wilt in China: History, current status, and future perspectives. Frontiers of Plant Science 8, 1549

[28] Jiang, Y., Huang, M., Zhang, M., Lan, J., Wang, W., Tao, X., Liu, Y., 2018. Transcriptome analysis provides novel insights into high-soil-moisture-elevated susceptibility to Ralstonia solanacearum infection in ginger (Zingiber officinale Roscoe cv. Southwest). Plant Physiology and Biochemistry 132, 547–556

[29] Kabacoff, R., ed., 2015. R in Action, 2nd Edition. Manning Publications Co., CTUnited States.

[30] Kahm, M., Hasenbrink, G., Lichtenberg-Fraté, H., Ludwig, J., Kschischo, M., 2010. grofit: Fitting Biological Growth Curves with R. Journal of Statistical Software 33, 1–21

[31] Kearns, D.B., 2010. A field guide to bacterial swarming motility. Nature Reviews. Microbiology 8, 634–644

[32] Kramer, P.J., 1983. Water Relations of Plants. Elsevier Science, Oxford.

[33] Kwak, M.J., Kong, H.G., Choi, K., Kwon, S.K., Song, J.Y., Lee, J., Lee, P.A., Choi, S.Y., Seo, M., Lee, H.J., Jung, E.J., Park, H., Roy, N., Kim, H., Lee, M.M., Rubin, E.M., Lee, S.W., Kim, J.F., 2018. Rhizosphere microbiome structure alters to enable wilt resistance in tomato. Nature Biotechnology 36, 1100–1109

[34] Larson, J.E., Funk, J.L., 2016. Seedling root responses to soil moisture and the identification of a belowground trait spectrum across three growth forms. New Phytologist 210, 827–838

[35] Lê, S., Josse, J., Husson, F., 2008. FactoMineR: an R package for multivariate analysis. Journal of Statistical Software 25, 1–18

[36] Lee, S.M., Kong, H.G., Song, G.C., Ryu, C.M., 2021. Disruption of Firmicutes and Actinobacteria abundance in tomato rhizosphere causes the incidence of bacterial wilt disease. ISME Journal 15, 330–347

[37] Li, S., Liu, Y., Wang, J., Yang, L., Zhang, S., Xu, C., Ding, W., 2017a. Soil acidification aggravates the occurrence of bacterial wilt in south China. Frontiers in Microbiology 8, 703

[38] Li, S., Xu, C., Wang, J., Guo, B., Yang, L., Chen, J., Ding, W., 2017b. Cinnamic, myristic and fumaric acids in tobacco root exudates induce the infection of plants by Ralstonia solanacearum. Plant and Soil 412, 381–395

[39] Li, Y., Uddin, W., Kaminski, J.E., 2014. Effects of relative humidity on infection, colonization and conidiation of Magnaporthe orzyae on perennial ryegrass. Plant Pathology 63, 590–597

[40] Mainiero, R., Kazda, M., 2005. Effects of Carex rostrata on soil oxygen in relation to soil moisture. Plant and Soil 270, 311–320

[41] Mansfield, J., Genin, S., Magori, S., Citovsky, V., Sriariyanum, M., Ronald, P., Dow, M., Verdier, V., Beer, S.V., Machado, M.A., Toth, I., Salmond, G., Foster, G.D., 2012. Top 10 plant pathogenic bacteria in molecular plant pathology. Molecular Plant Pathology 13, 614–629

[42] Mondal, B., Bhattacharya, I., Khatua, D.C., 2014. Incidence of bacterial wilt disease in West Bengal, India. Academia Journal of Agricultural Research 2, 139–146.

[43] Orr, R., Nelson, P.N., 2018. Impacts of soil abiotic attributes on Fusarium wilt, focusing on bananas. Applied Soil Ecology 132, 20–33

[44] Panchal, S., Chitrakar, R., Thompson, B.K., Obulareddy, N., Roy, D., Hambright, W.S., Melotto, M., 2016. Regulation of stomatal defense by air relative humidity. Plant Physiology 172, 2021–2032

[45] Pansu, M., Gautheyrou, J., eds., 2006. Handbook of Soil Analysis: Mineralogical, Organic and Inorganic Methods. Springer, Berlin, Heidelberg.

[46] Patro, S.G.K., Sahu, K.K., 2015. Normalization: a preprocessing stage. ArXiv 1503.06462.

[47] Peyraud, R., Cottret, L., Marmiesse, L., Genin, S., 2018. Control of primary metabolism by a virulence regulatory network promotes robustness in a plant pathogen. Nature Communications 9, 418

[48] Peyraud, R., Cottret, L., Marmiesse, L., Gouzy, J., Genin, S., 2016. A resource allocation trade-off between virulence and proliferation drives metabolic versatility in the plant pathogen Ralstonia solanacearum. PLoS Pathogens 12, e1005939

[49] Pimentel, C.S., Ayres, M.P., 2018. Latitudinal patterns in temperature-dependent growth rates of a forest pathogen. Journal of Thermal Biology 72, 39–43

[50] R Core Team, 2020. The R Stats Package.

[51] Rahman, K.A., Othman, R., 2020. Influence of pH levels on disease development in oil palm seedling roots infected with Ganoderma boninensis. Rhizosphere 13, 100181

[52] Raza, W., Wang, J., Wu, Y., Ling, N., Wei, Z., Huang, Q., Shen, Q., 2016. Effects of volatile organic compounds produced by Bacillus amyloliquefaciens on the growth and virulence traits of tomato bacterial wilt pathogen Ralstonia solanacearum. Applied Microbiology and Biotechnology 100, 7639–7650

[53] Satou, M., Kubota, M., Nishi, K., 2006. Measurement of horizontal and vertical movement of Ralstonia solanacearum in soil. Journal of Phytopathology 154, 592–597

[54] Schandry, N., 2017. A practical guide to visualization and statistical analysis of R. solanacearum infection data using R. Frontiers of Plant Science 8, 623

[55] Schönfeld, J., Heuer, H., van Elsas, J.D., Smalla, K., 2003. Specific and sensitive detection of Ralstonia solanacearum in soil on the basis of PCR amplification of fliC fragments. Applied and Environmental Microbiology 69, 7248–7256

[56] Sinha, R., Gupta, A., Senthil-Kumar, M., 2016. Understanding the impact of drought on foliar and xylem invading bacterial pathogen stress in chickpea. Frontiers of Plant Science 7, 902

[57] Siregar, B.A., Giyanto, Hidayat, S.H., Siregar, I.Z., Tjahjono, B., 2020. Epidemiology of bacterial wilt disease on Eucalyptus pellita F. Muell. in Indonesia. IOP Conference Series: Earth and Environmental Science 468, 012033.

[58] Smilanick, J.L., Mansour, M.F., 2007. Influence of temperature and humidity on survival of Penicillium digitatum and Geotrichum citri-aurantii. Plant Disease 91, 990–996

[59] Trivedi, P., Leach, J.E., Tringe, S.G., Sa, T., Singh, B.K., 2020. Plant-microbiome interactions: from community assembly to plant health. Nature Reviews Microbiology 18, 607–621

[60] van Elsas, J.D., Kastelein, P., van Bekkum, P., van der Wolf, J.M., de Vries, P.M., van Overbeek, L.S., 2000. Survival of Ralstonia solanacearum Biovar 2, the causative agent of potato brown rot, in field and microcosm soils in temperate climates. Phytopathology 90, 1358–1366

[61] Velásquez, A.C., Castroverde, C.D.M., He, S.Y., 2018. Plant-pathogen warfare under changing climate conditions. Current Biology 28, R619–R634

[62] Wang, R., Zhang, H., Sun, L., Qi, G., Chen, S., Zhao, X., 2017. Microbial community composition is related to soil biological and chemical properties and bacterial wilt outbreak. Scientific Reports 7, 343

[63] Wei, Z., Friman, V.P., Pommier, T., Geisen, S., Jousset, A., Shen, Q., 2020. Rhizosphere immunity: targeting the underground for sustainable plant health management. Frontiers of Agricultural Science and Engineering 7, 317–328

[64] Wei, Z., Gu, Y., Friman, V.P., Kowalchuk, G.A., Xu, Y., Shen, Q., Jousset, A., 2019. Initial soil microbiome composition and functioning predetermine future plant health. Science Advances 5, eaaw0759.

[65] Wei, Z., Hu, J., Gu, Y., Yin, S., Xu, Y., Jousset, A., Shen, Q., Friman, V.P., 2018. Ralstonia solanacearum pathogen disrupts bacterial rhizosphere microbiome during an invasion. Soil Biology & Biochemistry 118, 8–17

[66] Wei, Z., Huang, J., Yang, T., Jousset, A., Xu, Y., Shen, Q., Friman, V.P., 2017. Seasonal variation in the biocontrol efficiency of bacterial wilt is driven by temperature-mediated changes in bacterial competitive interactions. Journal of Applied Ecology 5, 1440–1448

[67] Wei, Z., Huang, J.F., Hu, J., Gu, Y.A., Yang, C.L., Mei, X.L., Shen, Q.R., Xu, Y.C., Friman, V.P., 2015a. Altering transplantation time to avoid periods of high temperature can efficiently reduce bacterial wilt disease incidence with tomato. PLoS One 10, e0139313

[68] Wei, Z., Yang, T., Friman, V.P., Xu, Y., Shen, Q., Jousset, A., 2015b. Trophic network architecture of root-associated bacterial communities determines pathogen invasion and plant health. Nature Communications 6, 8413

[69] Wei, Z., Yang, X., Yin, S., Shen, Q., Ran, W., Xu, Y., 2011. Efficacy of Bacillus-fortified organic fertiliser in controlling bacterial wilt of tomato in the field. Applied Soil Ecology 48, 152–159

[70] Wen, T., Zhao, M., Liu, T., Huang, Q., Yuan, J., Shen, Q., 2020. High abundance of Ralstonia solanacearum changed tomato rhizosphere microbiome and metabolome. BMC Plant Biology 20, 166

[71] Wickham, H., Chang, W., Henry, L., Pedersen, T.L., Takahashi, K., Wilke, C., Woo, K., Yutani, H., Dunnington, D., RStudio, 2020. ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics.

[72] Wu, X., Li, H., Wang, Y., Zhang, X., 2020. Effects of bio-organic fertiliser fortified by Bacillus cereus QJ-1 on tobacco bacterial wilt control and soil quality improvement. Biocontrol Science and Technology 30, 351–369

[73] Xin, X.F., Nomura, K., Aung, K., Velásquez, A.C., Yao, J., Boutrot, F., Chang, J.H., Zipfel, C., He, S.Y., 2016. Bacteria establish an aqueous living space in plants crucial for virulence. Nature 539, 524–529

Acknowledgments

We thank Dr. Alexandre Jousset and Dr. Zhipeng Liu for helpful discussions. This research was financially supported by the National Natural Science Foundation of China (41922053, 42090062, 31972504 and 42007038), and the Fundamental Research Funds for the Central Universities (KJQN202116-KJQN202117, KYXK202009-KYXK202012), the Natural Science Foundation of Jiangsu Province (BK20190518, BK20180527 and BK20200533), the China Postdoctoral Science Foundation (2019M651848) and technically supported by the Bioinformatics Center of Nanjing Agricultural University. S.G. is funded by the NWO-Veni grant (016.Veni.181.078 to S.G.). V.F. is funded by the Royal Society (RSG\R1\180213 and CHL\R1\180031) and jointly by a grant from UKRI, Defra, and the Scottish Government, under the Strategic Priorities Fund Plant Bacterial Diseases program me (BB/T010606/1) at the University of York.

Conflict of interest

The authors declare that there are no relevant conflicts of interest.

RIGHTS & PERMISSIONS

2021 Higher Education Press