Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Virulence of banana wilt-causing fungal pathogen Fusarium oxysporum tropical race 4 is mediated by nitric oxide biosynthesis and accessory genes

Abstract

Fusarium wilt of banana, caused by Fusarium oxysporum f. sp. cubense (Foc), is one of the most damaging plant diseases known. Foc race 1 (R1) decimated the Gros Michel-based banana (Musa acuminata) trade, and now Foc tropical race 4 (TR4) threatens global production of its replacement, the Cavendish banana. Here population genomics revealed that all Cavendish banana-infecting Foc race 4 strains share an evolutionary origin distinct from that of R1 strains. Although TR4 lacks accessory chromosomes, it contains accessory genes at the ends of some core chromosomes that are enriched for virulence and mitochondria-related functions. Meta-transcriptomics revealed the unique induction of the entire mitochondrion-localized nitric oxide (NO) biosynthesis pathway upon TR4 infection. Empirically, we confirmed the unique induction of a NO burst in TR4, suggesting that nitrosative pressure may contribute to virulence. Targeted mutagenesis demonstrated the functional importance of fungal NO production and the accessory gene SIX4 as virulence factors.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: The most virulent Foc variant (TR4) has spread from Southeast Asia to Africa and Latin America.
Fig. 2: Foc phylogenomics and population structure.
Fig. 3: Genomic comparison reveals the attachment of accessory sequences to core chromosomes and the dynamics of these accessory sequences.
Fig. 4: The mitochondrion-localized nitrate/nitrite-dependent NO biosynthesis pathway and NO detoxification-related genes are significantly induced in TR4 at 18 HPI (created with BioRender.com).
Fig. 5: Plant hormone-induced fungal NO burst in TR4.
Fig. 6: Proposed TR4–Cavendish banana interaction mode (created with BioRender.com).

Similar content being viewed by others

Data availability

Genome sequences and annotations have been deposited in MycoCosm at the Joint Genome Institute (https://mycocosm.jgi.doe.gov/mycocosm/home) and at NCBI under the accession number PRJNA859936. Raw RNA-seq files for samples in this study were uploaded to the NCBI Sequence Read Archive and are publicly available under BioProject PRJNA1113144. Source data are provided with this paper.

Code availability

Computer codes generated for this study are available via GitHub at https://github.com/zya067025/Fusarium-oxysporum-f.-sp.-cubense----genomics.

References

  1. StokstadJul, E. Devastating banana disease may have reached Latin America, could drive up global prices. Science https://doi.org/10.1126/science.aay7681 (2019).

  2. Stover, R. H. Fusarial Wilt (Panama Disease) of Bananas and Other Musa Species (Commonwealth Mycological Institute, 1962).

  3. Buddenhagen, I. Understanding strain diversity in Fusarium oxysporum f. sp. cubense and history of introduction of ‘tropical race 4’ to better manage banana production. In III International Symposium on Banana: ISHS-ProMusa Symposium on Recent Advances in Banana Crop Protection for Sustainable Production and Improved Livelihoods (eds Jones, D. & Van den Bergh I.) 193–204 (White River, 2009).

  4. Viljoen, A., Ma, L.-J. & Molina, A. B. in Emerging Plant Diseases and Global Food Security (eds Ristaino, J. B. & Records, A.) 159–184 (The American Phytopathological Society, 2020).

  5. Maymon, M., Sela, N., Shpatz, U., Galpaz, N. & Freeman, S. The origin and current situation of Fusarium oxysporum f. sp. cubense tropical race 4 in Israel and the Middle East. Sci. Rep. 10, 1590 (2020).

  6. Maymon, M. et al. First report of Fusarium oxysporum f. sp. cubense tropical race 4 causing Fusarium wilt of Cavendish bananas in Israel. Plant Dis. 102, 2655 (2018).

    Article  Google Scholar 

  7. García-Bastidas, F. et al. First report of Fusarium wilt tropical race 4 in Cavendish bananas caused by Fusarium odoratissimum in Colombia. Plant Dis. 104, 994–994 (2020).

    Article  Google Scholar 

  8. Acuña, R. et al. First report of Fusarium oxysporum f. sp. cubense tropical race 4, causing Fusarium wilt in Cavendish bananas in Peru. Plant Dis. https://doi.org/10.1094/pdis-09-21-1951-pdn (2021).

  9. Ma, L.-J. et al. Fusarium pathogenomics. Annu. Rev. Microbiol. 67, 399–416 (2013).

    Article  CAS  PubMed  Google Scholar 

  10. Dean, R. et al. The top 10 fungal pathogens in molecular plant pathology. Mol. Plant Pathol. 13, 414–430 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Ma, L.-J. et al. Comparative genomics reveals mobile pathogenicity chromosomes in Fusarium. Nature 464, 367–373 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Yang, H., Yu, H. & Ma, L.-J. Accessory chromosomes in Fusarium oxysporum. Phytopathology 110, 1488–1496 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Zhang, Y. & Ma, L. J. Deciphering pathogenicity of Fusarium oxysporum from a phylogenomics perspective. Adv. Genet. 100, 179–209 (2017).

    Article  CAS  PubMed  Google Scholar 

  14. Does, H. & Rep, M. in Plant Fungal Pathogens (eds Bolton, M. & Thomma, B.) 427–437 (Humana Press, 2012).

  15. van Dam, P. et al. Effector profiles distinguish formae speciales of Fusarium oxysporum. Environ. Microbiol. 18, 4087–4102 (2016).

    Article  PubMed  Google Scholar 

  16. Ploetz, R. C. Fusarium wilt of banana is caused by several pathogens referred to as Fusarium oxysporum f. sp. cubense. Phytopathology 96, 653–656 (2006).

    Article  PubMed  Google Scholar 

  17. Ploetz, R. C. Management of Fusarium wilt of banana: a review with special reference to tropical race 4. Crop Prot. 73, 7–15 (2015).

    Article  CAS  Google Scholar 

  18. Bentley, S., Pegg, K., Moore, N., Davis, R. & Buddenhagen, I. Genetic variation among vegetative compatibility groups of Fusarium oxysporum f. sp. cubense analyzed by DNA fingerprinting. Phytopathology 88, 1283–1293 (1998).

    Article  CAS  PubMed  Google Scholar 

  19. Katan, T. & Primo, P. D. Current status of vegetative compatibility groups in Fusarium oxysporum: supplement (1999). Phytoparasitica 27, 273–277 (1999).

    Article  Google Scholar 

  20. Moore, N., Pegg, K., Allen, R. & Irwin, J. Vegetative compatibility and distribution of Fusarium oxysporum f. sp. cubense in Australia. Aust. J. Exp. Agric. 33, 797–802 (1993).

    Article  Google Scholar 

  21. Fourie, G., Steenkamp, E., Gordon, T. & Viljoen, A. Evolutionary relationships among the Fusarium oxysporum f. sp. cubense vegetative compatibility groups. Appl. Environ. Microbiol. 75, 4770–4781 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Warmington, R. J. et al. High-quality draft genome sequence of the causal agent of the current Panama disease epidemic. Microbiol. Resour. Announc. 8, e00904-19 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Yun, Y. et al. Genome data of Fusarium oxysporum f. sp. cubense race 1 and tropical race 4 isolates using long-read sequencing. Mol. Plant Microbe Interact. 32, 1270–1272 (2019).

    Article  CAS  PubMed  Google Scholar 

  24. Leiva, A. M. et al. Draft genome sequence of Fusarium oxysporum f. sp. cubense tropical race 4 from Peru, obtained by nanopore and illumina hybrid assembly. Microbiol. Resour. Announc. 11, e00347-22 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Zheng, S.-J. et al. New geographical insights of the latest expansion of Fusarium oxysporum f. sp. cubense tropical race 4 into the greater Mekong subregion. Front. Plant Sci. 9, 457 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  26. O’Donnell, K., Kistler, H. C., Cigelnik, E. & Ploetz, R. C. Multiple evolutionary origins of the fungus causing Panama disease of banana: concordant evidence from nuclear and mitochondrial gene genealogies. Proc. Natl Acad. Sci. USA 95, 2044–2049 (1998).

    Article  PubMed  PubMed Central  Google Scholar 

  27. Chellapan, B. V., van Dam, P., Rep, M., Cornelissen, B. J. & Fokkens, L. Non-canonical Helitrons in Fusarium oxysporum. Mob. DNA 7, 27 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Marcos, A. T. et al. Nitric oxide synthesis by nitrate reductase is regulated during development in A. spergillus. Mol. Microbiol. 99, 15–33 (2016).

    Article  CAS  PubMed  Google Scholar 

  29. Brodhun, F. et al. An iron 13 S-lipoxygenase with an α-linolenic acid specific hydroperoxidase activity from Fusarium oxysporum. PLoS ONE 8, e64919 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Thatcher, L. F., Manners, J. M. & Kazan, K. Fusarium oxysporum hijacks COI1‐mediated jasmonate signaling to promote disease development in Arabidopsis. Plant J. 58, 927–939 (2009).

    Article  CAS  PubMed  Google Scholar 

  31. Guo, L. et al. Metatranscriptomic comparison of endophytic and pathogenic FusariumArabidopsis interactions reveals plant transcriptional plasticity. Mol. Plant Microbe Interact. 34, 1071–1083 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Sedlářová, M. et al. The role of nitric oxide in development and pathogenesis of biotrophic phytopathogens—downy and powdery mildews. Adv. Bot. Res. 77, 263–283 (2016).

    Article  Google Scholar 

  33. Kojima, H. et al. Bioimaging of nitric oxide with fluorescent indicators based on the rhodamine chromophore. Anal. Chem. 73, 1967–1973 (2001).

    Article  CAS  PubMed  Google Scholar 

  34. Lacza, Z. et al. The novel red-fluorescent probe DAR-4M measures reactive nitrogen species rather than NO. J. Pharmacol. Toxicol. Methods 52, 335–340 (2005).

    Article  CAS  PubMed  Google Scholar 

  35. Yu, H. et al. Conservation and expansion of transcriptional factor repertoire in the Fusarium oxysporum species complex. J. Fungi 9, 359 (2023).

    Article  CAS  Google Scholar 

  36. Ding, Y., Gardiner, D. M., Xiao, D. & Kazan, K. Regulators of nitric oxide signaling triggered by host perception in a plant pathogen. Proc. Natl Acad. Sci. USA 117, 11147–11157 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Hayashi, S. & Wu, H. C. Lipoproteins in bacteria. J. Bioenerg. Biomembr. 22, 451–471 (1990).

    Article  CAS  PubMed  Google Scholar 

  38. Schmidt, S. M. et al. MITEs in the promoters of effector genes allow prediction of novel virulence genes in Fusarium oxysporum. BMC Genomics 14, 119 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Widinugraheni, S. et al. A SIX1 homolog in Fusarium oxysporum f. sp. cubense tropical race 4 contributes to virulence towards Cavendish banana. PLoS ONE 13, e0205896 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. An, B. et al. The effector SIX8 is required for virulence of Fusarium oxysporum f. sp. cubense tropical race 4 to Cavendish banana. Fungal Biol. 123, 423–430 (2019).

    Article  CAS  PubMed  Google Scholar 

  41. Fokkens, L. & Rep, M. Population genomics reveals meiotic recombination in Fusarium oxysporum. Proc. Natl Acad. Sci. USA 120, e2309677120 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Sugui, J. A. et al. Identification and characterization of an Aspergillus fumigatus ‘supermater’ pair. MBio 2, 00234–11 (2011).

    Article  Google Scholar 

  43. Fayyaz, A. et al. Hiding in plain sight: genome-wide recombination and a dynamic accessory genome drive diversity in Fusarium oxysporum f. sp. ciceris. Proc. Natl Acad. Sci. USA 120, e2220570120 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Arasimowicz‐Jelonek, M. & Floryszak‐Wieczorek, J. Nitric oxide: an effective weapon of the plant or the pathogen? Mol. Plant Pathol. 15, 406–416 (2014).

    Article  PubMed  Google Scholar 

  45. Simontacchi, M., Galatro, A., Ramos-Artuso, F. & Santa-María, G. E. Plant survival in a changing environment: the role of nitric oxide in plant responses to abiotic stress. Front. Plant Sci. 6, 977 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Samalova, M. et al. Nitric oxide generated by the rice blast fungus Magnaporthe oryzae drives plant infection. N. Phytol. 197, 207–222 (2013).

    Article  CAS  Google Scholar 

  47. Sarkar, T. S., Biswas, P., Ghosh, S. K. & Ghosh, S. Nitric oxide production by necrotrophic pathogen Macrophomina phaseolina and the host plant in charcoal rot disease of jute: complexity of the interplay between necrotroph–host plant interactions. PLoS ONE 9, e107348 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  48. Turrion-Gomez, J. L. & Benito, E. P. Flux of nitric oxide between the necrotrophic pathogen Botrytis cinerea and the host plant. Mol. Plant Pathol. 12, 606–616 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Koren, S. et al. Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res. 27, 722–736 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Chin, C.-S. et al. Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data. Nat. Methods 10, 563–569 (2013).

    Article  CAS  PubMed  Google Scholar 

  51. Simpson, J. T. et al. ABySS: a parallel assembler for short read sequence data. Genome Res. 19, 1117–1123 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Cameron, D. L. et al. GRIDSS: sensitive and specific genomic rearrangement detection using positional de Bruijn graph assembly. Genome Res. 27, 2050–2060 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Sedlazeck, F. J. et al. Accurate detection of complex structural variations using single-molecule sequencing. Nat. Methods 15, 461–468 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Simão, F. A., Waterhouse, R. M., Ioannidis, P., Kriventseva, E. V. & Zdobnov, E. M. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31, 3210–3212 (2015).

    Article  PubMed  Google Scholar 

  55. Saha, S., Bridges, S., Magbanua, Z. V. & Peterson, D. G. Empirical comparison of ab initio repeat finding programs. Nucleic Acids Res. 36, 2284–2294 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Stanke, M. et al. AUGUSTUS: ab initio prediction of alternative transcripts. Nucleic Acids Res. 34, W435–W439 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Jones, P. et al. InterProScan 5: genome-scale protein function classification. Bioinformatics 30, 1236–1240 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Armenteros, J. A. et al. SignalP 5.0 improves signal peptide predictions using deep neural networks. Nat. Biotechnol. 37, 420–423 (2019).

    Article  Google Scholar 

  59. Krogh, A., Larsson, B., Von Heijne, G. & Sonnhammer, E. L. Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J. Mol. Biol. 305, 567–580 (2001).

    Article  CAS  PubMed  Google Scholar 

  60. Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  62. DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491–498 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Falush, D., Stephens, M. & Pritchard, J. K. Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164, 1567–1587 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Hoagland, D. R. & Arnon, D. I. The Water-Culture Method for Growing Plants without Soil (California Agricultural Experiment Station, 1950).

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  68. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Zhang, H. et al. Eight RGS and RGS-like proteins orchestrate growth, differentiation, and pathogenicity of Magnaporthe oryzae. PLoS Pathog. 7, e1002450 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors thank R. C. Ploetz, University of Florida, for providing Foc strains and J. Chambers, the director of the Microscopy Core Facility of the Institution for Applied Life Sciences at University of Massachusetts, for his help with the confocal microscopy experiments. Data were analysed at the Massachusetts Green High Performance Computing Center (MGHPCC). The Guangdong Science and Technology Project (2019B1515120088, C.L.), the Laboratory of Lingnan Modern Agriculture Project (NT2021004, G.Y.), the Guangdong Provincial Special Fund for Modern Agriculture Industry Technology Innovation Teams (No. 2022KJ109, C.L.), the National Banana Industry and Technology System Project (nycytx-33) and the earmarked fund for CARS (CARS-31, G.Y.) provided financial support. This project was funded by the Natural Science Foundation (IOS-165241, L.-J.M.) and the National Research Initiative Competitive Grants Program (MAS00532 and MAS00496, L.-J.M.) from the USDA National Institute of Food and Agriculture. The work (proposal: 10.46936/10.25585/60008191, L.-J.M.) conducted by the US Department of Energy Joint Genome Institute (https://ror.org/04xm1d337), a DOE Office of Science User Facility, is supported by the Office of Science of the US Department of Energy operated under contract no. DE-AC02-05CH11231 (I.V.G). L.-J.M. is also supported by the National Eye Institute of the US National Institutes of Health under award number R01EY030150. H.Y. is also supported by the Lotta M. Crabtree Fellowship and the Constantine J. Gilgut Fellowship. The funding bodies played no role in the design of the study, the collection, analysis and interpretation of the data, or the writing of the manuscript.

Author information

Authors and Affiliations

Authors

Contributions

L.-J.M., Y.Z., G.Y., C.L., and A.V. conceived the research strategies. L.-J.M., C.L. and A.V. supervised the project. Y.Z. and L.-J.M. wrote the manuscript with input from all authors. Y.Z., S.L., M.Z., G.L. and C.Z. conducted NO detection and mutagenesis studies. Y.Z., H.Y., S.H. and I.V.G. analysed the data. Y.Z., S.L, G.L., M.Z., C.Z., K.W. and M.L. validated the experiments. D.M., C.L. and A.V. collected and provided the strains.

Corresponding authors

Correspondence to Altus Viljoen, Chunyu Li or Li-Jun Ma.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Microbiology thanks Jeffrey Coleman, Donald Gardiner and Martijn Rep for their contribution to the peer review of this work. Peer reviewer reports are available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 SNP density on chromosomes 3 and 6 of two Foc TR4 and two VCG 0121 strains.

Tracks from the inside to outside are as follows: four histogram circles of SNP distribution on chromosomes 3 and 6 for 811-VCG01213-TR4, 789-VCG01213-16-TR4, CAV2318-VCG0121 and CAV180-VCG0121; and II5 chromosomes 3 and 6 (blue) with accessory sequences (orange) as a reference. The mating-type (MAT) locus MAT1 on the core chromosomal region of chromosome 6 and Helitron transposable elements on accessory region of chromosome 3 are indicated.

Extended Data Fig. 2 Comparative meta-transcriptomics of Cavendish bananas infected with R1 (GD02) and TR4 (II5).

a, Infection stages of GFP-tagged Foc TR4 II5 in banana roots. Root materials were collected, and the infection process was monitored under a microscope after inoculation at different stages of infection. Left to right: At 18 HPI, Foc TR4 spores began to germinate and cover the surface of the root. The pathogen continued to grow, and hyphae penetrated the root. At approximately 32 HPI, many hyphae were evident in the xylem, and visible dark spots appeared on the root. At 56 HPI, there was a large increase in fungal biomass and necrotic root symptoms. b, Foc race 1 has weaker colonization capability than Foc TR4 during the infection process. Percentage of mapped reads derived from fungi and plants in the infection time course in the race 1–banana (red) and Foc TR4–banana (green) interactions. Data presented are the mean +/− standard deviations from three biological replicates at each time point.

Extended Data Fig. 3 Expression profiles of 18 fungal co-expressed gene clusters based on TR4 and R1 shared orthologs using a global hierarchical clustering algorithm.

The x-axis shows the time points of Cavendish banana infection with R1 (GD02) and TR4 (II5). The y-axis shows the Z-scores of gene expression. Color scale indicates the correlation of expression between genes and the cluster centroids. Genes with an expression correlation with a centroid lower than 0.8 are shown in gray.

Extended Data Fig. 4 Fungal functional network of Foc-C5, Foc-C7 and Foc-C14 that were significantly induced by 18 HPI in TR4 compared to R1.

a, Three fungal co-expressed gene clusters were significantly induced at 18 HPI in TR4 compared to R1. b, Foc-C5 (510 genes) was enriched for electron transfer activity (corrected P = 0.01), Foc-C7 (846 genes) for heme-copper terminal oxidase activity (corrected P = 0.03) and NADPH quinone reductase activity (corrected P = 0.01) and Foc-C14 (694 genes) for regulation of nitrogen compound metabolic process (corrected P = 0.05). Collectively, these three clusters are enriched for genes involved in NO biosynthesis and denitrification. GO annotations and genes are presented as nodes. The annotations are highlighted with different colors based on the distribution of the nodes in the network. The size of the node is proportional to the number of connections. Two-sided Benjamini-Hochberg corrected Fisher’s exact test was performed to identify enriched GO terms.

Extended Data Fig. 5 qRT-PCR of banana phytoglobin genes.

qRT-PCR confirming that all three genes were significantly induced in Cavendish banana at 18 HPI with TR4 strain II5 compared with R1 strain GD02. Data are shown as box plots of three biological replicates (n=3) with the interquartile range as the upper and lower confines of the box and the median as a solid line within the box. Our RNA-seq data identified one banana phytoglobin gene, Ma02_g10610, as one of the top 10 most highly induced plant genes. Asterisks indicate significantly induced phytoglobin gene expression (* = P < 0.05, Student’s t test) in Foc TR4–inoculated Cavendish banana. All statistical tests carried out were two-sided.

Source data

Extended Data Fig. 6 Expression profiles of 24 plant-expressed gene clusters.

The x-axis represents the time point of Cavendish banana infection with R1 (GD02) and TR4 (II5). The y-axis shows the Z-score of gene expression. Color scale indicates the correlation of expression between genes and the cluster centroids. Genes with a correlation of expression with a centroid < 0.8 are shown in gray.

Extended Data Fig. 7 Mutants of fungal genes involved in the fungal NO biosynthesis pathway have reduced fungal virulence and NO production.

a, The ΔGene_2699 and ΔGene_9725 mutants were generated in the Foc TR4 II5 WT background using the standard one-step gene replacement strategy69. The complemented strains ΔGene_2699-C (complemented FocΔGene_2699 strain) and ΔGene_9725-C (complemented FocΔGene_9725 strain) were generated using whole genes and their native promoters combined with the neomycin resistance gene. Cavendish banana plantlets with four or five leaves were inoculated with mock (H2O) or treated soil samples harboring conidia from different strains (5,000 conidia/g soil). The disease index (DI) distribution (top panel; see Methods) was calculated among 20 inoculated plants based on the DI from 0–4: 0, no symptoms; 1, some brown spots in the inner rhizome; 2, <25% of the inner rhizome showing browning; 3, up to 75% of the inner rhizome showing browning; and 4, 100% of the inner rhizome and pseudostem dark brown (considered dead). The cross sections were sampled from inoculated plantlets (bottom panel) at 30 days post inoculation. The extent of discoloration is correlated with the DI distribution shown in the top panel. b, Analysis of NO production by TR4 WT, ΔGene_2699 and ΔGene_9725 mutants with NO-sensitive fluorescent dye DAR-4M-AM as a probe; NO production was measured at 6 hours after the JA stimulation. Data are shown as box plots with the interquartile range as the upper and lower confines of the box and the median as a solid line within the box. Different letters indicate significant differences according to one-way ANOVA (P < 0.05). Each experiment included three biological replicates and was repeated independently at least three times.

Source data

Extended Data Fig. 8 Phylogeny of expressed, accessory transcription factor (TF) genes encoding the GAL4-like Zn2-C6 binuclear cluster DNA-binding domain.

The phylogenetic tree (generated using the maximum-likelihood method) reveals that the GAL4-like domain–containing TFs that expanded in TR4 reside in three major clades. Clade III comprises 26 GAL4-like TFs that are phylogenetically close to FgZC1 (FGSG_05068), a transcription factor known to play an important role in host-mediated fungal NO production and virulence in F. graminearum. In addition to these expressed accessory genes, this analysis included functionally characterized genes with a GAL4-like domain. Ab, Alternaria brassicicola; Cl, Colletotrichum lindemuthianum; Fg, Fusarium graminearum; Fo, Fusarium oxysporum; Fv, Fusarium verticillioides; Ff, Fusarium fujikuroi; Mo, Magnaporthe oryzae; Vd, Verticillium dahliae.

Extended Data Fig. 9 Functional analysis of the fungal effector genes SIX1a and SIX4, which are present in the accessory region of chromosome 3 and were significantly induced upon host infection.

The ΔSIX1a and ΔSIX4 mutants were generated in the Foc TR4 II5 WT background using the standard one-step gene replacement strategy69. The complemented strains ΔSIX1a-C (complemented FocΔSIX1a strain) and ΔSIX4-C (complemented FocΔSIX4 strain) were generated using whole effector genes and their native promoters combined with the neomycin resistance gene. Cavendish banana plantlets with four or five leaves were inoculated with mock (H2O) or treated soil samples harboring conidia from different stains (5,000 conidia/g soil). The disease index (DI) distribution (top panel; see Methods) was calculated among 20 inoculated plants based on the DI from 0–−4: 0, no symptoms; 1, some brown spots in the inner rhizome; 2, <25% of the inner rhizome showing browning; 3, up to 75% of the inner rhizome showing browning; and 4, 100% of the inner rhizome and pseudostem dark brown (considered dead). The cross sections were sampled from inoculated plantlets (bottom panel) at 30 days post inoculation. The extent of discoloration is correlated with the DI distribution shown in the top panel.

Extended Data Fig. 10 Generation of gene mutants.

a, Schematic representation of the disruption strategy for SIX1a, SIX4, Gene_2699 and Gene_9725. Primer locations are marked with arrows. b, Plasmid map of pYF11. Restriction enzyme cutting sites are indicated. Features including antibiotic resistant genes and promoters are shown.

Supplementary information

Supplementary Information

Supplementary Fig. 1.

Reporting Summary

Peer Review File

Supplementary Tables 1–19

Supplementary Table 1 Fusarium oxysporum isolates used in this study, provided by Altus Vijoen (Stellenbosch University, South Africa), Randy C. Ploetz (University of Florida, USA) and Chunyu Li (Fruit Tree Research Institute, GDAAS, China). Supplementary Table 2 Summary of pathogenicity assay tests on banana cultivars with Foc TR4, STR4, VCG 0121 and race 1. Supplementary Table 3 II5 chromosomal accessory sequence size comparing to Fol 4287. Supplementary Table 4 Copy numbers of Helitrons by normalized read mappings. Supplementary Table 5 Genome statisitics of the de novo assembled Fusarium oxysporum f. sp. cubense strains. Supplementary Table 6 Heatmap of shared chromosomal accessory sequence size between II5 and other Foc strains. Supplementary Table 7 Statistics of the RNA-seq data and reads mapped to the reference genome II5 at different inoculation time points. Supplementary Table 8 Clusters of co-expressed banana and fungal genes. Supplementary Table 9 Presence/absence of 2,050 genes of three fungal gene clusters (Foc-C5, Foc-C7 and Foc-C14) in race 4 strains (six TR4, two VCG 0121 and two STR4). Supplementary Table 10 Expression of NO biosynthesis, denitrification and electron transport chain complex genes during infection. Supplementary Table 11 Top 20 expressed banana genes during host–pathogen interaction. Supplementary Table 12 Expressions of genes in plant-C22. Supplementary Table 13 Gene Ontology enrichment of 1,562 AS genes. Supplementary Table 14 GO enrichement of expressed 842 accessory sequence genes. Supplementary Table 15 Annotation for accessory genes enriched in obsolete electron transport. Supplementary Table 16 A list of selected F. oxysporum genomes for pan-geneme analysis. Supplementary Table 17 A list of 25 Foc-only gene familes and 189 Foc-race 4-only gene familes. Supplementary Table 18 Expression of fungal effectors in Foc TR4 accessory regions. Supplementary Table 19 PCR primers used in this study.

Source data

Source Data Fig. 1

Latitude and longitude of locations where strains were isolated.

Source Data Fig. 4

Expressions of genes involved in NO biosynthesis and denitrification.

Source Data Fig. 5

Raw fluorescence intensity of TR4 and R1 strains treated with/without MJ.

Source Data Extended Data Fig./Table 5

Relative expression of banana phytoglobin genes.

Source Data Extended Data Fig./Table 7

Raw fluorescence intensity of WT TR4 strain, gene mutants and their complement strains.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Y., Liu, S., Mostert, D. et al. Virulence of banana wilt-causing fungal pathogen Fusarium oxysporum tropical race 4 is mediated by nitric oxide biosynthesis and accessory genes. Nat Microbiol 9, 2232–2243 (2024). https://doi.org/10.1038/s41564-024-01779-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41564-024-01779-7

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing