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Genetic elucidation of interconnected antibiotic pathways mediating maize innate immunity

Abstract

Specialized metabolites constitute key layers of immunity that underlie disease resistance in crops; however, challenges in resolving pathways limit our understanding of the functions and applications of these metabolites. In maize (Zea mays), the inducible accumulation of acidic terpenoids is increasingly considered to be a defence mechanism that contributes to disease resistance. Here, to understand maize antibiotic biosynthesis, we integrated association mapping, pan-genome multi-omic correlations, enzyme structure–function studies and targeted mutagenesis. We define ten genes in three zealexin (Zx) gene clusters that encode four sesquiterpene synthases and six cytochrome P450 proteins that collectively drive the production of diverse antibiotic cocktails. Quadruple mutants in which the ability to produce zealexins (ZXs) is blocked exhibit a broad-spectrum loss of disease resistance. Genetic redundancies ensuring pathway resiliency to single null mutations are combined with enzyme substrate promiscuity, creating a biosynthetic hourglass pathway that uses diverse substrates and in vivo combinatorial chemistry to yield complex antibiotic blends. The elucidated genetic basis of biochemical phenotypes that underlie disease resistance demonstrates a predominant maize defence pathway and informs innovative strategies for transferring chemical immunity between crops.

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Fig. 1: A genetically variable cluster of four maize TPSs ensures the production of ZX precursors.
Fig. 2: Zx gene cluster II contains three 71Z-family cytochrome (CYP) P450s that catalyse the production of A- and D-series ZXs.
Fig. 3: Association mapping reveals that Zx gene cluster III contains three CYP81A-family P450s.
Fig. 4: Enzyme coexpression defines the role of Zx gene cluster III in antibiotic biosynthesis.
Fig. 5: ZX-pathway activation occurs during the large-scale reprograming of fungal-induced defences.
Fig. 6: The maize ZX pathway is a biosynthetic hourglass with genetic redundancy and enzyme promiscuity that ensures the production of protective antibiotic cocktails.

Data availability

Publicly available datasets used in the study include the National Center for Biotechnology Information (NCBI) Sequence Read Archive project ID SRP115041 and the MaizeGDB BLAST database (https://maizegdb.org/popcorn/main/index.php). Raw read sequences have been deposited at the NCBI Gene Expression Omnibus under accession numbers GSE138961 and GSE138962. Raw sequence data from the root microbiome are available at NCBI BioProject under accession number PRJNA580260. Raw proteomic mass spectra have been deposited at the Mass Spectrometry Interactive Virtual Environment repository (ftp://massive.ucsd.edu/MSV000084285). Maize-related germplasm used in this research have been previously described27,39,43,44,45,72,73 and can be obtained from US Department of Agriculture Germplasm Resources Information Network (https://www.ars-grin.gov) and the Maize Genetics Cooperation Stock Center (http://maizecoop.cropsci.uiuc.edu). Where possible, gene identifiers used throughout the manuscript were in reference to B73 RefGen_v4 (https://www.maizegdb.org/genome/assembly/Zm-B73-REFERENCE-GRAMENE-4.0), which was used as a foundation for the study. All data are available from the corresponding author on request.

Code availability

For the gene-duplication date estimations, scripts to perform translations, alignments and backtranslations as well as data files and BEAST control files have been deposited at GitHub (https://github.com/TomJKono/Zealexin_Dating).

References

  1. 1.

    Ritchie, H. & Roser, M. Land use. Our World in Data https://ourworldindata.org/land-use (2020).

  2. 2.

    Evenson, R. E. & Gollin, D. Assessing the impact of the green revolution, 1960 to 2000. Science 300, 758–762 (2003).

    CAS  Google Scholar 

  3. 3.

    Cartwright, D., Langcake, P., Pryce, R. J., Leworthy, D. P. & Ride, J. P. Chemical activation of host defence mechanisms as a basis for crop protection. Nature 267, 511–513 (1977).

    CAS  Google Scholar 

  4. 4.

    Snyder, B. A. & Nicholson, R. L. Synthesis of phytoalexins in Sorghum as a site-specific response to fungal ingress. Science 248, 1637–1639 (1990).

    CAS  Google Scholar 

  5. 5.

    Frey, M. et al. Analysis of a chemical plant defense mechanism in grasses. Science 277, 696–699 (1997).

    CAS  Google Scholar 

  6. 6.

    Goswami, R. S. & Kistler, H. C. Heading for disaster: Fusarium graminearum on cereal crops. Mol. Plant Pathol. 5, 515–525 (2004).

    CAS  Google Scholar 

  7. 7.

    Mueller, D. et al. Corn yield loss estimates due to diseases in the United States and Ontario, Canada from 2012 to 2015. Plant Health Prog. 17, 211–222 (2016).

    Google Scholar 

  8. 8.

    Genetics for a warming world. Nat. Genet. 51, 1195–1195 (2019).

  9. 9.

    Dixon, R. A. Natural products and plant disease resistance. Nature 411, 843–847 (2001).

    CAS  Google Scholar 

  10. 10.

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

    CAS  Google Scholar 

  11. 11.

    van Loon, L. C., Rep, M. & Pieterse, C. M. J. Significance of inducible defense related proteins in infected plants. Annu. Rev. Phytopathol. 44, 135–162 (2006).

    Google Scholar 

  12. 12.

    Moghe, G. D. & Kruse, L. H. The study of plant specialized metabolism: challenges and prospects in the genomics era. Am. J. Bot. 105, 959–962 (2018).

    Google Scholar 

  13. 13.

    Wouters, F. C., Blanchette, B., Gershenzon, J. & Vassao, D. G. Plant defense and herbivore counter-defense: benzoxazinoids and insect herbivores. Phytochem. Rev. 15, 1127–1151 (2016).

    CAS  Google Scholar 

  14. 14.

    Meihls, L. N. et al. Natural variation in maize aphid resistance is associated with 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one glucoside methyltransferase activity. Plant Cell 25, 2341–2355 (2013).

    CAS  Google Scholar 

  15. 15.

    Fraenkel, G. S. The raison d’etre of secondary plant substances; these odd chemicals arose as a means of protecting plants from insects and now guide insects to food. Science 129, 1466–1470 (1959).

    CAS  Google Scholar 

  16. 16.

    Schmelz, E. A. et al. Biosynthesis, elicitation and roles of monocot terpenoid phytoalexins. Plant J. 79, 659–678 (2014).

    CAS  Google Scholar 

  17. 17.

    Vaughan, M. M. et al. Accumulation of terpenoid phytoalexins in maize roots is associated with drought tolerance. Plant Cell Environ. 38, 2195–2207 (2015).

    CAS  Google Scholar 

  18. 18.

    Ding, Y. et al. Multiple genes recruited from hormone pathways partition maize diterpenoid defences. Nat. Plants 10, 1043–1056 (2019).

    Google Scholar 

  19. 19.

    Casas, M. I. et al. Identification and characterization of maize salmon silks genes involved in insecticidal maysin biosynthesis. Plant Cell 28, 1297–1309 (2016).

    CAS  Google Scholar 

  20. 20.

    Degenhardt, J. Indirect defense responses to herbivory in grasses. Plant Physiol. 149, 96–102 (2009).

    CAS  Google Scholar 

  21. 21.

    Zila, C. T., Samayoa, L. F., Santiago, R., Butron, A. & Holland, J. B. A genome-wide association study reveals genes associated with Fusarium ear rot resistance in a maize core diversity panel. G3 3, 2095–2104 (2013).

    Google Scholar 

  22. 22.

    Wiesner-Hanks, T. & Nelson, R. Multiple disease resistance in plants. Annu Rev. Phytopathol. 54, 229–252 (2016).

    CAS  Google Scholar 

  23. 23.

    Stagnati, L. et al. A genome wide association study reveals markers and genes associated with resistance to Fusarium verticillioides infection of seedlings in a maize diversity panel. G3 9, 571–579 (2019).

    CAS  Google Scholar 

  24. 24.

    Banerjee, A. & Hamberger, B. P450s controlling metabolic bifurcations in plant terpene specialized metabolism. Phytochem. Rev. 17, 81–111 (2018).

    CAS  Google Scholar 

  25. 25.

    Karunanithi, P. S. & Zerbe, P. Terpene synthases as metabolic gatekeepers in the evolution of plant terpenoid chemical diversity. Front. Plant Sci. 10, 1166 (2019).

    Google Scholar 

  26. 26.

    Block, A. K., Vaughan, M. M., Schmelz, E. A. & Christensen, S. A. Biosynthesis and function of terpenoid defense compounds in maize (Zea mays). Planta 249, 21–30 (2019).

    CAS  Google Scholar 

  27. 27.

    Springer, N. M. et al. The maize W22 genome provides a foundation for functional genomics and transposon biology. Nat. Genet. 50, 1282–1288 (2018).

    CAS  Google Scholar 

  28. 28.

    Ding, Y. Z. et al. Selinene volatiles are essential precursors for maize defense promoting fungal pathogen resistance. Plant Physiol. 175, 1455–1468 (2017).

    CAS  Google Scholar 

  29. 29.

    Huffaker, A. et al. Novel acidic sesquiterpenoids constitute a dominant class of pathogen-induced phytoalexins in maize. Plant Physiol. 156, 2082–2097 (2011).

    CAS  Google Scholar 

  30. 30.

    Mafu, S. et al. Discovery, biosynthesis and stress-related accumulation of dolabradiene-derived defenses in maize. Plant Physiol. 176, 2677–2690 (2018).

    CAS  Google Scholar 

  31. 31.

    Mao, H., Liu, J., Ren, F., Peters, R. J. & Wang, Q. Characterization of CYP71Z18 indicates a role in maize zealexin biosynthesis. Phytochemistry 121, 4–10 (2016).

    CAS  Google Scholar 

  32. 32.

    Basse, C. W. Dissecting defense-related and developmental transcriptional responses of maize during Ustilago maydis infection and subsequent tumor formation. Plant Physiol. 138, 1774–1784 (2005).

    CAS  Google Scholar 

  33. 33.

    Kollner, T. G. et al. Protonation of a neutral (S)-β-bisabolene intermediate is involved in (S)-β-macrocarpene formation by the maize sesquiterpene synthases TPS6 and TPS11. J. Biol. Chem. 283, 20779–20788 (2008).

    Google Scholar 

  34. 34.

    Christensen, S. A. et al. Fungal and herbivore elicitation of the novel maize sesquiterpenoid, zealexin A4, is attenuated by elevated CO2. Planta 247, 863–873 (2018).

    CAS  Google Scholar 

  35. 35.

    van der Linde, K., Kastner, C., Kumlehn, J., Kahmann, R. & Doehlemann, G. Systemic virus-induced gene silencing allows functional characterization of maize genes during biotrophic interaction with Ustilago maydis. N. Phytol. 189, 471–483 (2011).

    Google Scholar 

  36. 36.

    Shen, Q. et al. CYP71Z18 overexpression confers elevated blast resistance in transgenic rice. Plant Mol. Biol. 100, 579–589 (2019).

    CAS  Google Scholar 

  37. 37.

    Medema, M. H. et al. Minimum information about a biosynthetic gene cluster. Nat. Chem. Biol. 11, 625–631 (2015).

    CAS  Google Scholar 

  38. 38.

    Kersten, R. D., Diedrich, J. K., Yates, J. R. 3rd & Noel, J. P. Mechanism-based post-translational modification and inactivation in terpene synthases. ACS Chem. Biol. 10, 2501–2511 (2015).

    CAS  Google Scholar 

  39. 39.

    Flint-Garcia, S. A. et al. Maize association population: a high-resolution platform for quantitative trait locus dissection. Plant J. 44, 1054–1064 (2005).

    CAS  Google Scholar 

  40. 40.

    Kremling, K. A. G. et al. Dysregulation of expression correlates with rare-allele burden and fitness loss in maize. Nature 555, 520–523 (2018).

    CAS  Google Scholar 

  41. 41.

    Jones, C. G. et al. Sandalwood fragrance biosynthesis involves sesquiterpene synthases of both the terpene synthase (TPS)-a and TPS-b subfamilies, including santalene synthases. J. Biol. Chem. 286, 17445–17454 (2011).

    CAS  Google Scholar 

  42. 42.

    Swigonova, Z. et al. Close split of Sorghum and maize genome progenitors. Genome Res. 14, 1916–1923 (2004).

    CAS  Google Scholar 

  43. 43.

    Lee, M. et al. Expanding the genetic map of maize with the intermated B73 x Mo17 (IBM) population. Plant Mol. Biol. 48, 453–461 (2002).

    CAS  Google Scholar 

  44. 44.

    McMullen, M. D. et al. Genetic properties of the maize nested association mapping population. Science 325, 737–740 (2009).

    CAS  Google Scholar 

  45. 45.

    Eichten, S. R. et al. B73-Mo17 near-isogenic lines demonstrate dispersed structural variation in maize. Plant Physiol. 156, 1679–1690 (2011).

    CAS  Google Scholar 

  46. 46.

    Suzuki, R., Iijima, M., Okada, Y. & Okuyama, T. Chemical constituents of the style of Zea mays L. with glycation inhibitory activity. Chem. Pharm. Bull. 55, 153–155 (2007).

    CAS  Google Scholar 

  47. 47.

    Ahmad, S. et al. Benzoxazinoid metabolites regulate innate immunity against aphids and fungi in maize. Plant Physiol. 157, 317–327 (2011).

    CAS  Google Scholar 

  48. 48.

    Smissman, E. E., Lapidus, J. B. & Beck, S. D. Corn plant resistance factor. J. Org. Chem. 22, 220–220 (1957).

    CAS  Google Scholar 

  49. 49.

    Pollastri, S. & Tattini, M. Flavonols: old compounds for old roles. Ann. Bot. 108, 1225–1233 (2011).

    CAS  Google Scholar 

  50. 50.

    Lange, B. M. The evolution of plant secretory structures and emergence of terpenoid chemical diversity. Annu. Rev. Plant Biol. 66, 139–159 (2015).

    CAS  Google Scholar 

  51. 51.

    Balmer, D., de Papajewski, D. V., Planchamp, C., Glauser, G. & Mauch-Mani, B. Induced resistance in maize is based on organ-specific defence responses. Plant J. 74, 213–225 (2013).

    CAS  Google Scholar 

  52. 52.

    Yang, F. et al. A maize gene regulatory network for phenolic metabolism. Mol. Plant 10, 498–515 (2017).

    CAS  Google Scholar 

  53. 53.

    Benson, J. M., Poland, J. A., Benson, B. M., Stromberg, E. L. & Nelson, R. J. Resistance to gray leaf spot of maize: genetic architecture and mechanisms elucidated through nested association mapping and near-isogenic line analysis. PLoS Genet. 11, e1005045 (2015).

    Google Scholar 

  54. 54.

    Kump, K. L. et al. Genome-wide association study of quantitative resistance to southern leaf blight in the maize nested association mapping population. Nat. Genet. 43, 163–168 (2011).

    CAS  Google Scholar 

  55. 55.

    Zuo, W. et al. A maize wall-associated kinase confers quantitative resistance to head smut. Nat. Genet. 47, 151–157 (2015).

    CAS  Google Scholar 

  56. 56.

    Hamilton, R. H. A corn mutant deficient in 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one with an altered tolerance of atrazine. Weeds 12, 27–30 (1964).

    CAS  Google Scholar 

  57. 57.

    Meunier, B., de Visser, S. P. & Shaik, S. Mechanism of oxidation reactions catalyzed by cytochrome P450 enzymes. Chem. Rev. 104, 3947–3980 (2004).

    CAS  Google Scholar 

  58. 58.

    Henriques de Jesus, M. P. R. et al. Tat proteins as novel thylakoid membrane anchors organize a biosynthetic pathway in chloroplasts and increase product yield 5-fold. Metab. Eng. 44, 108–116 (2017).

    CAS  Google Scholar 

  59. 59.

    Laursen, T. et al. Characterization of a dynamic metabolon producing the defense compound dhurrin in Sorghum. Science 354, 890–893 (2016).

    CAS  Google Scholar 

  60. 60.

    Nelson, R., Wiesner-Hanks, T., Wisser, R. & Balint-Kurti, P. Navigating complexity to breed disease-resistant crops. Nat. Rev. Genet. 19, 21–33 (2018).

    CAS  Google Scholar 

  61. 61.

    Chappell, J. & Hahlbrock, K. Transcription of plant defense genes in response to UV-light or fungal elicitor. Nature 311, 76–78 (1984).

    CAS  Google Scholar 

  62. 62.

    Facchini, P. J. & Chappell, J. Gene family for an elicitor-induced sesquiterpene cyclase in tobacco. Proc. Natl Acad. Sci. USA 89, 11088–11092 (1992).

    CAS  Google Scholar 

  63. 63.

    Koutsoudis, M. D., Tsaltas, D., Minogue, T. D. & von Bodman, S. B. Quorum-sensing regulation governs bacterial adhesion, biofilm development, and host colonization in Pantoea stewartii subspecies stewartii. Proc. Natl Acad. Sci. USA 103, 5983–5988 (2006).

    CAS  Google Scholar 

  64. 64.

    Doblas-Ibanez, P. et al. Dominant, heritable resistance to Stewart’s wilt in maize is associated with an enhanced vascular defense response to infection with Pantoea stewartii. Mol. Plant Microbe Interact. 32, 1581–1597 (2019).

    CAS  Google Scholar 

  65. 65.

    Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).

    CAS  Google Scholar 

  66. 66.

    Kim, D., Landmead, B. & Salzberg, S. L. HISAT: a fast spliced aligner with low memory requirements. Nat. Methods 12, 357–360 (2015).

    CAS  Google Scholar 

  67. 67.

    Tarasov, A., Vilella, A. J., Cuppen, E., Nijman, I. J. & Prins, P. Sambamba: fast processing of NGS alignment formats. Bioinformatics 31, 2032–2034 (2015).

    CAS  Google Scholar 

  68. 68.

    Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).

    CAS  Google Scholar 

  69. 69.

    Anders, S. & Huber, W. Differential expression analysis for sequence count data. Genome Biol. 11, R106 (2010).

    CAS  Google Scholar 

  70. 70.

    Kim, D. et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 14, R36 (2013).

    Google Scholar 

  71. 71.

    Anders, S., Pyl, P. T. & Huber, W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics 31, 166–169 (2015).

    CAS  Google Scholar 

  72. 72.

    Schnable, P. S. et al. The B73 maize genome: complexity, diversity, and dynamics. Science 326, 1112–1115 (2009).

    CAS  Google Scholar 

  73. 73.

    Sun, S. et al. Extensive intraspecific gene order and gene structural variations between Mo17 and other maize genomes. Nat. Genet. 50, 1289–1295 (2018).

    CAS  Google Scholar 

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Acknowledgements

We thank A. Steinbrenner, J. Chan, K. O’Leary, M. Broemmer, H. Riggleman, S. Reyes and S. Delgado for help with planting, treatments and sampling (UCSD); L. Smith (UCSD) for shared UCSD Biology Field Station management; B. Hamberger (Michigan State University) for the ElHMGR gene. This work was partially supported by the USDA-ARS National Programs for Food Safety and Plant Genetic Resources, Genomics and Genetic Improvement (to M.M.V., M.G.B. and S.A.C.). Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the USDA. Research was supported by grants from the National Science Foundation, Division of Integrative Organismal Systems (NSF-IOS) (grant no. 1936492 to B.Y. and grant no. 1546899 to S.P.B.), USDA NIFA AFRI (grant no. 2018-67013-28125 to A.H. and E.S.) for sesquiterpenoids, NSF Plant-Biotic Interactions Program (grant no. 1758976 to E.S. and P.Z.) for diterpenoids, NSF Faculty Early Career Development Program (grant no. 1943591 to A.H.), the DOE Joint Genome Institute Community Science Program (JGI-CSP) (grant nos. CSP 2568 (to P.Z., J.B., E.S. and A.H.) and CSP 503420 (to A.H. and E.S.)) and fellowships provided by the NSF Graduate Research Fellowship Program (to K.M.M.), the U.C. Davis Innovation Institute for Food and Health (IIFH) Fellowship Program (to K.M.M. and P.Z.), the USDA NIFA Predoctoral Fellowship Program (award no. 2019-67011-29544, to K.M.M.) and a Fulbright Research Grant (E0581299, to M.B.).

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Y.D., P.R.W., E.P., P.Z., J.S., J.B., K.D., E.A.S. and A.H. designed the experiments and analysed the data. Y.D., E.P., S.A.C., T.G.K., P.Z., K.A.K. and E.S.B. designed, performed and analysed the transcriptome data. Y.D., E.S., A.S.K., K.M.M., P.Z., A.H. and E.A.S. performed MS experiments and MS-related metabolite data analysis. Y.D., E.S., K.M.M., P.Z., E.A.S. and A.H. performed and analysed the enzyme coexpression data. Z.S., A.-D.T. and S.P.B. analysed the combined proteome and transcriptome dataset. T.K. calculated estimates of gene evolution dates. D.R.N. assigned subfamily names for P450 proteins. M.M.V. and M.G.B. generated and analysed the root microbiome data. B.Y., S.N.C. and P.R.W. designed gRNA constructs and generated the zx1zx2zx3 and zx1zx2zx3zx4 maize mutants. J.S. and M.B. performed metabolite purifications and analysed the NMR data. Y.D. and P.R.W. performed the in vitro and in vivo antibiotic resistance assays. Y.D., P.R.W., E.P., P.Z., E.A.S. and A.H. wrote the manuscript with input from all of the authors.

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Correspondence to Alisa Huffaker.

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Ding, Y., Weckwerth, P.R., Poretsky, E. et al. Genetic elucidation of interconnected antibiotic pathways mediating maize innate immunity. Nat. Plants 6, 1375–1388 (2020). https://doi.org/10.1038/s41477-020-00787-9

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