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Phytophthora sojae boosts host trehalose accumulation to acquire carbon and initiate infection

Abstract

Successful infection by pathogenic microbes requires effective acquisition of nutrients from their hosts. Root and stem rot caused by Phytophthora sojae is one of the most important diseases of soybean (Glycine max). However, the specific form and regulatory mechanisms of carbon acquired by P. sojae during infection remain unknown. In the present study, we show that P. sojae boosts trehalose biosynthesis in soybean through the virulence activity of an effector PsAvh413. PsAvh413 interacts with soybean trehalose-6-phosphate synthase 6 (GmTPS6) and increases its enzymatic activity to promote trehalose accumulation. P. sojae directly acquires trehalose from the host and exploits it as a carbon source to support primary infection and development in plant tissue. Importantly, GmTPS6 overexpression promoted P. sojae infection, whereas its knockdown inhibited the disease, suggesting that trehalose biosynthesis is a susceptibility factor that can be engineered to manage root and stem rot in soybean.

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Fig. 1: PsAvh413 contributes to the virulence of Phytophthora pathogens.
Fig. 2: PsAvh413 physically associates with soybean GmTPS6 in vitro and in vivo.
Fig. 3: PsAvh413 expression enhances trehalose accumulation in planta by activating the enzymatic activity of the functional GmTPS6.
Fig. 4: Trehalose serves as a source of nutrition for P. sojae.
Fig. 5: P. sojae can absorb trehalose both in vitro and in vivo.
Fig. 6: GmTPS6 acts as a susceptibility factor on P. sojae infection.

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Data availability

The sequencing data have been deposited in the Sequence Read Archive database with BioProject accession no. PRJNA972839. The sgRNA target sites were designed online (http://grna.ctegd.uga.edu/instructions.html) and the potential off-target effects were checked using the FungiDB (www.fungidb.org) alignment search tool (BLASTN) against the P. sojae genome. GmTPS6 homologous genes in N. benthamiana were identified by search using its genome sequence draft (https://solgenomics.net/organism/Nicotiana_benthamiana/genome). All other data are available from the authors on request. Source data are provided with this paper.

References

  1. Kamoun, S. et al. The top 10 oomycete pathogens in molecular plant pathology. Mol. Plant Pathol. 16, 413–434 (2015).

    PubMed  Google Scholar 

  2. Derevnina, L. et al. Emerging oomycete threats to plants and animals. Philos. Trans. R. Soc. Lond. B Biol. Sci. 371, 20150459 (2016).

  3. Yang, X., Tyler, B. M. & Hong, C. An expanded phylogeny for the genus Phytophthora. IMA Fungus 8, 355–384 (2017).

    PubMed  PubMed Central  Google Scholar 

  4. Haas, B. J. et al. Genome sequence and analysis of the Irish potato famine pathogen Phytophthora infestans. Nature 461, 393–398 (2009).

    CAS  PubMed  Google Scholar 

  5. Tyler, B. M. et al. Phytophthora genome sequences uncover evolutionary origins and mechanisms of pathogenesis. Science 313, 1261–1266 (2006).

    CAS  PubMed  Google Scholar 

  6. Goodwin, S. B. The population genetics of phytophthora. Phytopathology 87, 462–473 (1997).

    CAS  PubMed  Google Scholar 

  7. Hamilton, C. D., Steidl, O. R., MacIntyre, A. M., Hendrich, C. G. & Allen, C. Ralstonia solanacearum depends on catabolism of myo-inositol, sucrose, and trehalose for virulence in an infection stage-dependent manner. Mol. Plant Microbe Interact. 34, 669–679 (2021).

  8. Jiang, Y. et al. Plants transfer lipids to sustain colonization by mutualistic mycorrhizal and parasitic fungi. Science 356, 1172–1175 (2017).

    CAS  PubMed  Google Scholar 

  9. Wang, W. et al. Nutrient exchange and regulation in arbuscular mycorrhizal symbiosis. Mol. Plant 10, 1147–1158 (2017).

    CAS  PubMed  Google Scholar 

  10. Judelson, H. S. & Ah-Fong, A. M. V. Exchanges at the plant-oomycete interface that influence disease. Plant Physiol. 179, 1198–1211 (2019).

    CAS  PubMed  Google Scholar 

  11. Wang, S. et al. Delivery of cytoplasmic and apoplastic effectors from Phytophthora infestans haustoria by distinct secretion pathways. N. Phytol. 216, 205–215 (2017).

    CAS  Google Scholar 

  12. Rodenburg, S. Y. A., Seidl, M. F., de Ridder, D. & Govers, F. Genome-wide characterization of Phytophthora infestans metabolism: a systems biology approach. Mol. Plant Pathol. 19, 1403–1413 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Rodenburg, S. Y. A., Seidl, M. F., de Ridder, D. & Govers, F. Uncovering the role of metabolism in oomycete–host interactions using genome-scale metabolic models. Front. Microbiol. 12, 748178 (2021).

    PubMed  PubMed Central  Google Scholar 

  14. Lunn, J. E., Delorge, I., Figueroa, C. M., Van Dijck, P. & Stitt, M. Trehalose metabolism in plants. Plant J. 79, 544–567 (2014).

    CAS  PubMed  Google Scholar 

  15. Cabib, E. & Leloir, L. F. The biosynthesis of trehalose phosphate. J. Biol. Chem. 231, 259–275 (1958).

    CAS  PubMed  Google Scholar 

  16. MacIntyre, A. M. et al. Trehalose synthesis contributes to osmotic stress tolerance and virulence of the bacterial wilt pathogen Ralstonia solanacearum. Mol. Plant Microbe 33, 462–473 (2020).

    CAS  Google Scholar 

  17. Vanaporn, M. & Titball, R. W. Trehalose and bacterial virulence. Virulence 11, 1192–1202 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Djonovic, S. et al. Trehalose biosynthesis promotes Pseudomonas aeruginosa pathogenicity in plants. PLoS Pathog. 9, e1003217 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Foster, A. J., Jenkinson, J. M. & Talbot, N. J. Trehalose synthesis and metabolism are required at different stages of plant infection by Magnaporthe grisea. EMBO J. 22, 225–235 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Song, X. S. et al. Trehalose 6-phosphate phosphatase is required for development, virulence and mycotoxin biosynthesis apart from trehalose biosynthesis in Fusarium graminearum. Fungal Genet. Biol. 63, 24–41 (2014).

    CAS  PubMed  Google Scholar 

  21. Poueymiro, M. et al. A Ralstonia solanacearum type III effector directs the production of the plant signal metabolite trehalose-6-phosphate. mBio 5, e02065-14 (2014).

    PubMed  PubMed Central  Google Scholar 

  22. Jones, J. D. & Dangl, J. L. The plant immune system. Nature 444, 323–329 (2006).

    CAS  PubMed  Google Scholar 

  23. El Kasmi, F., Horvath, D. & Lahaye, T. Microbial effectors and the role of water and sugar in the infection battle ground. Curr. Opin. Plant Biol. 44, 98–107 (2018).

    CAS  PubMed  Google Scholar 

  24. Gupta, P. K., Balyan, H. S. & Gautam, T. SWEET genes and TAL effectors for disease resistance in plants: present status and future prospects. Mol. Plant Pathol. 22, 1014–1026 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Cox, K. L. et al. TAL effector driven induction of a SWEET gene confers susceptibility to bacterial blight of cotton. Nat. Commun. 8, 15588 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Sonnewald, S. et al. Regulation of cell wall-bound invertase in pepper leaves by Xanthomonas campestris pv. vesicatoria type three effectors. PLoS ONE 7, e51763 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Breia, R. et al. Plant SWEETs: from sugar transport to plant–pathogen interaction and more unexpected physiological roles. Plant Physiol. 186, 836–852 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Gentzel, I. et al. Dynamic nutrient acquisition from a hydrated apoplast supports biotrophic proliferation of a bacterial pathogen of maize. Cell Host Microbe 30, 502–517.e504 (2022).

    CAS  PubMed  Google Scholar 

  29. Zhang, Y. et al. A gRNA-tRNA array for CRISPR-Cas9 based rapid multiplexed genome editing in Saccharomyces cerevisiae. Nat. Commun. 10, 1053 (2019).

    PubMed  PubMed Central  Google Scholar 

  30. Ramon, M. et al. Extensive expression regulation and lack of heterologous enzymatic activity of the class II trehalose metabolism proteins from Arabidopsis thaliana. Plant Cell Environ. 32, 1015–1032 (2009).

    CAS  PubMed  Google Scholar 

  31. Wang, Y., Tyler, B. M. & Wang, Y. Defense and counterdefense during plant-pathogenic oomycete infection. Annu. Rev. Microbiol. 73, 667–696 (2019).

    CAS  PubMed  Google Scholar 

  32. Fernandez, O., Bethencourt, L., Quero, A., Sangwan, R. S. & Clement, C. Trehalose and plant stress responses: friend or foe? Trends Plant Sci. 15, 409–417 (2010).

    CAS  PubMed  Google Scholar 

  33. Schluepmann, H., Pellny, T., van Dijken, A., Smeekens, S. & Paul, M. Trehalose 6-phosphate is indispensable for carbohydrate utilization and growth in Arabidopsis thaliana. Proc. Natl Acad. Sci. USA 100, 6849–6854 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Ponnu, J., Wahl, V. & Schmid, M. Trehalose-6-phosphate: connecting plant metabolism and development. Front. Plant Sci. 2, 70 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Wang, W. et al. Trehalose-6-phosphate phosphatase E modulates ABA-controlled root growth and stomatal movement in Arabidopsis. J. Integr. Plant Biol. 62, 1518–1534 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Wang, X., Du, Y. & Yu, D. Trehalose phosphate synthase 5-dependent trehalose metabolism modulates basal defense responses in Arabidopsis thaliana. J. Integr. Plant Biol. 61, 509–527 (2019).

    CAS  PubMed  Google Scholar 

  37. Zhao, Y. et al. The Phytophthora effector Avh94 manipulates host jasmonic acid signaling to promote infection. J. Integr. Plant Biol. 64, 2199–2210 (2022).

    CAS  PubMed  Google Scholar 

  38. Lowe-Power, T. M. et al. Metabolomics of tomato xylem sap during bacterial wilt reveals Ralstonia solanacearum produces abundant putrescine, a metabolite that accelerates wilt disease. Environ. Microbiol. 20, 1330–1349 (2018).

    CAS  PubMed  Google Scholar 

  39. Chary, S. N., Hicks, G. R., Choi, Y. G., Carter, D. & Raikhel, N. V. Trehalose-6-phosphate synthase/phosphatase regulates cell shape and plant architecture in Arabidopsis. Plant Physiol. 146, 97–107 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Delorge, I., Figueroa, C., Feil, R., Lunn, J. & Van Dijck, P. Trehalose-6-phosphate synthase 1 is not the only active TPS in Arabidopsis thaliana. Biochem. J. 466, 283–290 (2015).

    CAS  PubMed  Google Scholar 

  41. Singh, V. et al. TREHALOSE PHOSPHATE SYNTHASE11-dependent trehalose metabolism promotes Arabidopsis thaliana defense against the phloem-feeding insect Myzus persicae. Plant J. 67, 94–104 (2011).

    CAS  PubMed  Google Scholar 

  42. Vishal, B., Krishnamurthy, P., Ramamoorthy, R. & Kumar, P. P. OsTPS8 controls yield-related traits and confers salt stress tolerance in rice by enhancing suberin deposition. N. Phytol. 221, 1369–1386 (2019).

    CAS  Google Scholar 

  43. Wang, C. L., Zhang, S. C., Qi, S. D., Zheng, C. C. & Wu, C. A. Delayed germination of Arabidopsis seeds under chilling stress by overexpressing an abiotic stress inducible GhTPS11. Gene 575, 206–212 (2016).

    CAS  PubMed  Google Scholar 

  44. Xian, L. et al. A bacterial effector protein hijacks plant metabolism to support pathogen nutrition. Cell Host Microbe 28, 548–557.e7 (2020).

    CAS  PubMed  Google Scholar 

  45. Subramoni, S., Nathoo, N., Klimov, E. & Yuan, Z. C. Agrobacterium tumefaciens responses to plant-derived signaling molecules. Front. Plant Sci. 5, 322 (2014).

    PubMed  PubMed Central  Google Scholar 

  46. Gao, C. Genome engineering for crop improvement and future agriculture. Cell 184, 1621–1635 (2021).

    CAS  PubMed  Google Scholar 

  47. Fang, Y. & Tyler, B. M. Efficient disruption and replacement of an effector gene in the oomycete Phytophthora sojae using CRISPR/Cas9. Mol. Plant Pathol. 17, 127–139 (2016).

    CAS  PubMed  Google Scholar 

  48. Huang, J. et al. An oomycete plant pathogen reprograms host pre-mRNA splicing to subvert immunity. Nat. Commun. 8, 2051 (2017).

    PubMed  PubMed Central  Google Scholar 

  49. Zhang, P. et al. The WY domain in the Phytophthora effector PSR1 is required for infection and RNA silencing suppression activity. N. Phytol. 223, 839–852 (2019).

    CAS  Google Scholar 

  50. Qiao, Y., Shi, J., Zhai, Y., Hou, Y. & Ma, W. Phytophthora effector targets a novel component of small RNA pathway in plants to promote infection. Proc. Natl Acad. Sci. USA 112, 5850–5855 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Lu, Q. et al. Arabidopsis homolog of the yeast TREX-2 mRNA export complex: components and anchoring nucleoporin. Plant J. 61, 259–270 (2010).

    CAS  PubMed  Google Scholar 

  52. Earley, K. W. et al. Gateway-compatible vectors for plant functional genomics and proteomics. Plant J. 45, 616–629 (2006).

    CAS  PubMed  Google Scholar 

  53. Chen, C. et al. Pyrophosphate-fructose 6-phosphate 1-phosphotransferase (PFP1) regulates starch biosynthesis and seed development via heterotetramer formation in rice (Oryza sativa L.). Plant Biotechnol. J. 18, 83–95 (2020).

    CAS  PubMed  Google Scholar 

  54. Zhou, J. et al. Differential phosphorylation of the transcription factor WRKY33 by the protein kinases CPK5/CPK6 and MPK3/MPK6 cooperatively regulates camalexin biosynthesis in Arabidopsis. Plant Cell 32, 2621–2638 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Dangl, J. L. & Jones, J. D. Plant pathogens and integrated defence responses to infection. Nature 411, 826–833 (2001).

    CAS  PubMed  Google Scholar 

  56. Gui, X. et al. Phytophthora effector PSR1 hijacks the host pre-mRNA splicing machinery to modulate small RNA biogenesis and plant immunity. Plant Cell 34, 3443–3459 (2022).

    PubMed  PubMed Central  Google Scholar 

  57. Ma, Z. C. et al. A Phytophthora sojae glycoside hydrolase 12 protein is a major virulence factor during soybean infection and is recognized as a PAMP. Plant Cell 27, 2057–2072 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Clough, S. J. & Bent, A. F. Floral dip: a simplified method for Agrobacterium-mediated transformation of Arabidopsis thaliana. Plant J. 16, 735–743 (1998).

    CAS  PubMed  Google Scholar 

  59. Xie, X. et al. CRISPR-GE: a convenient software toolkit for CRISPR-based genome editing. Mol. Plant 10, 1246–1249 (2017).

    CAS  PubMed  Google Scholar 

  60. Bai, M. et al. Generation of a multiplex mutagenesis population via pooled CRISPR-Cas9 in soya bean. Plant Biotechnol. J. 18, 721–731 (2020).

    CAS  PubMed  Google Scholar 

  61. Jansing, J., Sack, M., Augustine, S. M., Fischer, R. & Bortesi, L. CRISPR/Cas9-mediated knockout of six glycosyltransferase genes in Nicotiana benthamiana for the production of recombinant proteins lacking beta-1,2-xylose and core alpha-1,3-fucose. Plant Biotechnol. J. 17, 350–361 (2019).

    CAS  PubMed  Google Scholar 

  62. Fiehn, O., Kopka, J., Trethewey, R. N. & Willmitzer, L. Identification of uncommon plant metabolites based on calculation of elemental compositions using gas chromatography and quadrupole mass spectrometry. Anal. Chem. 72, 3573–3580 (2000).

    CAS  PubMed  Google Scholar 

  63. Kim, D., Paggi, J. M., Park, C., Bennett, C. & Salzberg, S. L. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat. Biotechnol. 37, 907–915 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. Trapnell, C. et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat. Biotechnol. 28, 511–515 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. Muller, M. & Munne-Bosch, S. Rapid and sensitive hormonal profiling of complex plant samples by liquid chromatography coupled to electrospray ionization tandem mass spectrometry. Plant Methods 7, 37 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  66. Kumar, S., Stecher, G., Li, M., Knyaz, C. & Tamura, K. MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 35, 1547–1549 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank Y. Wang (Nanjing Agricultural University) for providing the P. Sojae isolate P6497-RFP, H. Zhang (Shanghai Normal University, China) for soybean CRISPR–Cas9 vector and S. Dong (Nanjing Agricultural University) for helpful discussions. This work was supported by grants from the National Natural Science Foundation of China (grant nos. 32001883 and 32072502) and the Science and Technology Commission of Shanghai Municipality (grant no. 18DZ2260500).

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Authors and Affiliations

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Contributions

Y.L.Q. conceived and designed the experiments. X.G.Z., D.F., D.L., H.X.J., L.G., J.N.Z., T.Y.Z. and Q.Y.H. performed the experiments. A.M., E.T.W., Q.H.S., J.M.Z., Y.C.W. and W.B.M. provided the suggestion for this research. X.G.Z. analysed the experimental data. Y.L.Q. and X.G.Z. wrote the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Yongli Qiao.

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The authors declare no competing interests.

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Nature Microbiology thanks Caitilyn Allen, Eleanor Gilroy 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 Expression profile of PsAvh413 at the transcriptional levels.

a, Alignment of the full-length amino acid sequences of PsAvh413 in four P. sojae isolates using Clustal Omega. SP, signal peptide region; RXLR, RxLR/dEER motifs were indicated. Identical and similar residues are shaded black. Two point mutations (M1 and M2) of PsAvh413 was generated by analysis of amino acid sequences. n = 3 biologically independent samples for each treatment. b, Expression profile of PsAvh413 in susceptible soybean HC6 during P. sojae infection. Total RNA was extracted from mycelia (MY) or infected soybean roots at 0.5, 0.75, 1, 1.5, 12, 24 and 48 h post inoculation (hpi). Transcript levels of PsAvh413 were determined by qRT-PCR. The P. sojae Actin gene (VMD GeneID: 108986) was used as an internal control. c, Schematic representation of effector PsAvh413 deletion using the CRISPR-Cas9 technique. The detected primers used in PCR were shown at the positions of the forward (F) and reverse (R). d, The agarose gel shows a PCR result of PsAvh413 loci from individual P. sojae mutants. WT represents wild-type P. sojae strain P6497. M, DNA marker. e, Growth of PsAvh413-knockout mutants. Photographs were taken at 6 days after Wild-type (WT) and PsAvh413-knockout transformants incubated on 10% vegetable juice (V8) medium at 25°C. f, Colony growth was calculated based on the diameters of colonies. n = 4 biologically independent medium for each treatment. g, Western blot analysis of N. benthamiana carrying PsAvh413 and its mutant using anti-FLAG antibody. Equal loading was confirmed by Coomassie brilliant blue (CBB) staining of total proteins. Data in b and f represent the means ± s.e.m. Different letters indicate significantly different groups in f (P < 0.01, one-way ANOVA, Tukey HSD). The experiment was repeated three times with similar results.

Source data

Extended Data Fig. 2 Overexpression of PsAvh413 affected plant development and defense response in Arabidopsis.

a, Arabidopsis leaves expressing PsAvh413 increase the susceptibility to P. parasitica. Photos were taken at 2 dpi. b, c, Statistics analysis of relative biomass quantification (b) and lesion length (c) of a. PpUBC2 and AtActin genes were used as internal controls. n = 3 (b) and n = 15 (c) biologically independent leaves for each treatment. d, Western blot analysis of transgenic Arabidopsis plants carrying PsAvh413 using anti-HA antibody. Equal loading was confirmed by Coomassie brilliant blue (CBB) staining of total proteins. e, Representative images of wild-type plants and PsAvh413-transgenic Arabidopsis lines. PsAvh413 expression perturbed the growth and development of Arabidopsis plants. Four-week-old Arabidopsis seedling grown in soil were photographed (lower panel). Six-week-old Arabidopsis plants grown in soil were photographed (upper panel). Different letters indicate significantly different groups in b-c (P < 0.01, ANOVA, Tukey HSD). Data in b represent mean ± s.e.m. Boxplot centre lines in c show median value; upper and lower bounds show the 25th and 75th quantile, respectively; upper and lower whiskers show the largest and smallest values, respectively. The experiment was repeated three times with similar results.

Source data

Extended Data Fig. 3 Functional analysis of the soybean GmTPS6 gene.

a, Phylogeny analysis of GmTPS6 orthologs in soybean, N. benthamiana and Arabidopsis. Amino acid sequences of 20 soybean, 11 Arabidopsis and 16 N. benthamiana GmTPS6 homologs were aligned and the phylogenetic tree was generated using the Maximum-likelihood (ML) approach. The Glyma.07G172000 (GmTPS6) show higher amino acid identity with AtTPS6. b, Subcellular localization of GmTPS6 by confocal microscope. Scale bars, 20 μm. c, Expression profile of GmTPS6 in the susceptible soybean cultivar HC6 during P. sojae infection. Total RNA was extracted from infected soybean roots at 0, 0.5, 0.75, 1.0, 1.5, 12, 24 and 48 hpi. d, Expression profile of GmTPS6 at various plant tissue. Transcript levels of GmTPS6 were determined by qRT-PCR. GmEF1a gene was used as an internal control in c and d. n = 3 biologically independent samples for each treatment in c and d, mean ± s.e.m. The experiment was repeated twice with similar results.

Extended Data Fig. 4 Analysis of interactions between PsAvh413 and TPS6 proteins.

a, Schematic diagram showing the protein domains of GmTPS6 and its truncated mutants. Numbers underneath each construct indicate amino acid positions. b, Co-immunoprecipitation (Co-IP) assay displaying the interaction between GmTPS6-N or -C and PsAvh413. Immune complexes were pulled down using anti-MYC magnetic beads, and the coprecipitation of PsAvh413 was examined by western blotting using specific antibodies. c–e, Co-IP assays showing that PsAvh413 associates with AtTPS6 (c), AtTPS1 (d), and NbTPS6 (e). The experiment was performed in twice with similar results.

Extended Data Fig. 5 Disruptions of TPS1 gene using CRISPR-Cas9 in yeast.

a, Graphic representation of the three different gRNA expression systems for yeast TPS1 disruptions. b, Sanger sequencing in S. cerevisiae wild strain WT303 and ScTPS1-edited transformants. c, Yeast TPS1-edit strain (tps1-1Δ) is unable to grow on glucose.

Extended Data Fig. 6 Application of trehalose contributes to growth and infection of pathogens.

a, Trehalose can be used as nutritional source and contributes to three fungal pathogens growth and development. These fungi were cultured on Charlie solid medium without sucrose. b, Effect of trehalose concentration on lesion size and disease development in etiolated HC6 seedlings. H2O treated seedlings as control. c, Statistical analysis of lesion length and relative biomass data quantified in b. n = 3 (Relative biomass) and n = 7 (Lesion length) biologically independent seedlings for each treatment. d, Statistical analysis of lesion length quantified in Fig. 4e. n = 30 biologically independent seedlings for each treatment. e, g, Exogenous application of 1% trehalose markedly increased the development of disease symptoms in soybean (e) leaves upon P. sojae inoculation and Arabidopsis (g) leaves upon P. parasitica inoculation, respectively. f, h, Statistics analysis of lesion length and relative biomass data shown in (e, g). n = 3 (Relative biomass) and n = 10 (Lesion length) biologically independent leaves for each treatment in f and h. Different letters indicate significantly different groups in c (P < 0.01, Duncan’s multiple range test), and in f–h (P < 0.01, unpaired Student’s t test, two-tailed). Data of Relative biomass in c, f and h represent mean ± s.e.m. In c, d, f and h, boxplot centre lines show median value; upper and lower bounds show the 25th and 75th quantile, respectively; upper and lower whiskers show the largest and smallest values, respectively. Experiments were repeated twice with similar results.

Extended Data Fig. 7 Trehalose functions in contributing to growth and infection of pathogens.

a, Disease symptoms of the etiolated soybean seedlings treated with 26 mM trehalose or 50 μM T6P, and then inoculated with P. sojae strain P6497-RFP. Disease symptoms were photographed at 2 dpi. b, Statistical analysis of the relative biomass of P. sojae (Right) and lesion size data (left). n = 10 (Lesion length) and n = 3 (Relative biomass) biologically independent seedlings for each treatment. c, Effect of trehalose concentration on lesion size and disease development in etiolated HC6 seedlings inoculated with psavh413 mutant. d, Statistical analysis of lesion length and relative biomass data quantified in c. n = 7 (Lesion length) and n = 3 (Relative biomass) biologically independent seedlings for each treatment. The relative biomass of P. sojae in soybean hypocotyls was determined by DNA-based qPCR. PsActin and GmCYP2 genes were used as internal controls. Experiments were repeated twice with similar results. Different letters indicate significantly different groups in b (P < 0.01, one-way ANOVA, Tukey HSD). Data of Relative biomass in b and d represent mean ± s.e.m. In b and d, boxplot centre lines show median value; upper and lower bounds show the 25th and 75th quantile, respectively; upper and lower whiskers show the largest and smallest values, respectively. The experiment was repeated twice with similar results.

Extended Data Fig. 8 Analysis of differentially expressed genes in Col and PsAvh413-overexpressed plants.

a-b, Heatmaps (a) and volcano map (b) of up-regulated and downregulated in PsAvh413-overexpressed plants. c-d, Transcript abundance of pathogenesis-related proteins (c) or hormone-related genes (d) increase in PsAvh413-overexpressed plants. AT1G19610, Arabidopsis defensin-like protein; AT5G64120, Peroxidase superfamily protein; AT1G29380, Carbohydrate-binding X8 domain superfamily protein; AT2G38470, WRKY DNA-binding protein 33; AT2G34930, disease resistance family protein/LRR family protein; AT1G72940, Toll-Interleukin-Resistance (TIR) domain-containing protein; AT1G51800, Leucine-rich repeat protein kinase family protein; AT5G06720, peroxidase 2; AT5G59320, lipid transfer protein 3; AT3G04220, Disease resistance protein (TIR-NBS-LRR class) family; AT1G56510, Disease resistance protein (TIR-NBS-LRR class); AT1G22900, Disease resistance-responsive (dirigent-like protein) family protein; AT4G01250, WRKY family transcription factor; AT1G30135, jasmonate-zim-domain protein 8; AT3G23240, ethylene response factor 1; AT3G28910, myb domain protein 30; AT1G43160, related to AP2/ERF; AT2G44840, ethylene-responsive element binding factor 13; AT2G34600, jasmonate-zim-domain protein 7. n = 3 biologically independent samples for each treatment, means ± s.e.m. The experiment was replicated three times with similar results.

Extended Data Fig. 9 Molecular characteristics of PsTREs of P. sojae.

a, The agarose gel shows a PCR result of PsTREs loci from individual P. sojae mutants. Mutants pstre1-M1, pstre1-M11, pstre2-M1, and pstre2-M18 are homozygous. WT represents wild-type P. sojae strain P6497. b, Growth of PsTRE1/2-knockout transformants. Photographs were taken at 3 and 7 days after Wild-type (WT) and PsTRE1/2-knockout transformants incubated on 10% vegetable juice (V8) medium at 25°C. c, Colony growth was calculated based on the colony diameter at 5 days. n = 4 biologically independent medium for each treatment. d, Knockout of PsTRE1/2 in P. sojae did not affect the ability of their infection in soybean hypocotyls. Photos were taken at 2 dpi. e, Statistics analysis of lesion length (Right) and relative biomass quantification (Left) of d. n = 3 (Relative biomass) and n = 7 (Lesion length) biologically independent seedlings for each treatment. Different letters indicate significantly different groups in b (P < 0.01, one-way ANOVA, Tukey HSD). Data in c and e (Relative biomass) represent mean ± s.e.m. Boxplot centre lines in e show median value; upper and lower bounds show the 25th and 75th quantile, respectively; upper and lower whiskers show the largest and smallest values, respectively. The experiment was repeated three times with similar results.

Extended Data Fig. 10 NbTPS6 acts as a susceptibility factor against P. parasitica infection.

a, Relative transcript level of GmTPS6 in GmTPS6-overexpressing HC6 hairy roots. n = 3 biologically independent samples for each treatment. b, Overexpression of GmTPS6 in N. benthamiana promotes P. parasitica infection. Leaves transiently expressing YFP or GmTPS6 were inoculated P. parasitica. The pictures were taken at 48 hpi under ultraviolet lamp. c, Lesion length was measured and subjected to statistical analysis. d, Relative biomass of P. parasitica in YFP or GmTPS6-expressed leaves was determined by qPCR. n = 10 (b) and n = 3 (c) biologically independent leaves for each treatment. e, Expression of YFP and YFP-GmTPS6 was confirmed by western blotting using an anti-GFP antibody. Coomassie brilliant blue (CBB) staining as a loading control. The experiment was repeated twice with similar results. f, Phenotype of NbTPS6-silenced N. benthamiana plants using virus-induced gene silencing (VIGS) technique. Four DNA fragments of NbTPS6, including TRV2:VIGS1, TRV2:VIGS2, TRV2:VIGS3 and TRV2:VIGS4 were designed to silence NbTPS6, and the plants inoculated with TRV2:GFP as control. The pictures were taken at 14 dpi. g, Mild chlorotic mosaic symptoms were observed in N. benthamiana leaves inoculated the TRV2:GFP, TRV2:VIGS1, TRV2:VIGS2, TRV2:VIGS3 or TRV2:VIGS4 together with TRV1:00, respectively. V1, V2, V3, V4 represent VIGS1, VIGS2, VIGS3 and VIGS4 fragments of NbTPS6. The pictures were taken at 14 dpi. h, Relative transcript levels of NbTPS6 in four different combinations-silenced leaves. RNA samples were isolated from leaves co-infiltrated TRV1 together with TRV2:GFP, TRV2:VIGS1, TRV2:VIGS2, TRV2:VIGS3 and TRV2:VIGS4, respectively. NbActin gene was used as internal control. i, Disease symptoms of NbTPS6-silenced N. benthamiana leaves and challenged with P. parasitica. j, Lesion length was measured and subjected to statistical analysis. k, Relative biomass of P. parasitica was determined by qPCR. Scale bars: 1.0 cm. n = 3 (h, k) and n = 10 (j) biologically independent leaves for each treatment. Different letters indicate significantly different groups in a, c and d (P < 0.01, unpaired Student’s t test, two-tailed), and in h, i and j (P < 0.01, one-way ANOVA, Tukey HSD). Data of Relative biomass in a, d, h and k represent mean ± s.e.m. In c and j, boxplot centre lines show median value; upper and lower bounds show the 25th and 75th quantile, respectively; upper and lower whiskers show the largest and smallest values, respectively. The experiment was repeated three times with similar results.

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Supplementary Fig. 1.

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Supplementary Tables 1 and 2

Supplementary Table 1. Transcriptome data of the WT and PsAvh413 overexpressing line. Table 2. Primers used in the present study.

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Zhu, X., Fang, D., Li, D. et al. Phytophthora sojae boosts host trehalose accumulation to acquire carbon and initiate infection. Nat Microbiol 8, 1561–1573 (2023). https://doi.org/10.1038/s41564-023-01420-z

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