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.

  • Review Article
  • Published:

Pathways to engineering the phyllosphere microbiome for sustainable crop production

Nature Food volume 3, pages 997–1004 (2022)Cite this article

Subjects

Abstract

Current disease resistance breeding, which is largely dependent on the exploitation of resistance genes in host plants, faces the serious challenges of rapidly evolving phytopathogens. The phyllosphere is the largest biological surface on Earth and an untapped reservoir of functional microbiomes. The phyllosphere microbiome has the potential to defend against plant diseases. However, the mechanisms of how the microbiota assemble and function in the phyllosphere remain largely elusive, and this restricts the exploitation of the targeted beneficial microbes in the field. Here we review the endogenous and exogenous cues impacting microbiota assembly in the phyllosphere and how the phyllosphere microbiota in turn facilitate the disease resistance of host plants. We further construct a holistic framework by integrating of holo-omics, genetic manipulation, culture-dependent characterization and emerging artificial intelligence techniques, such as deep learning, to engineer the phyllosphere microbiome for sustainable crop production.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Fig. 1: Multiple cues influencing microbiota assembly in the phyllosphere.
Fig. 2: Phyllosphere microbiome-coordinated functioning in plant disease resistance.
Fig. 3: A holistic framework for mining the phyllosphere microbiome.
Fig. 4: Synergy between the phyllosphere microbiome studies and DL for smart agriculture.

Similar content being viewed by others

References

  1. Koskella, B. The phyllosphere. Curr. Biol. 30, R1143–R1146 (2020).

    Article  CAS  Google Scholar 

  2. Lu, N. et al. Improved estimation of aboveground biomass in wheat from RGB imagery and point cloud data acquired with a low-cost unmanned aerial vehicle system. Plant Methods 15, 17 (2019).

    Article  ADS  Google Scholar 

  3. Arye, G. C. & Harel, A. in Microbial Genomics in Sustainable Agroecosystems (eds Tripathi, V. et al.) 39–65 (Springer, 2020).

  4. Universal plant healthcare. Nat. Plants 6, 47 (2020).

  5. Fones, H. N. et al. Threats to global food security from emerging fungal and oomycete crop pathogens. Nat. Food 1, 332–342 (2020).

    Article  Google Scholar 

  6. Li, W., Deng, Y., Ning, Y., He, Z. & Wang, G. L. Exploiting broad-spectrum disease resistance in crops: from molecular dissection to breeding. Annu. Rev. Plant Biol. 71, 575–603 (2020).

    Article  CAS  Google Scholar 

  7. Matsumoto, H. et al. Bacterial seed endophyte shapes disease resistance in rice. Nat. Plants 7, 60–72 (2021).

    Article  CAS  Google Scholar 

  8. Thomazella, D. P. T. et al. Loss of function of a DMR6 ortholog in tomato confers broad-spectrum disease resistance. Proc. Natl Acad. Sci. USA 118, e2026152118 (2021).

    Article  Google Scholar 

  9. Guo, Y. Molecular design for rice breeding. Nat. Food 2, 849–849 (2021).

    Article  Google Scholar 

  10. Toju, H. et al. Core microbiomes for sustainable agroecosystems. Nat. Plants 4, 247–257 (2018).

    Article  Google Scholar 

  11. Berg, G. et al. Microbiome definition re-visited: old concepts and new challenges. Microbiome 8, 103 (2020).

    Article  Google Scholar 

  12. Carrion, V. J. et al. Pathogen-induced activation of disease-suppressive functions in the endophytic root microbiome. Science 366, 606–612 (2019).

    Article  ADS  CAS  Google Scholar 

  13. Chialva, M., Lanfranco, L. & Bonfante, P. The plant microbiota: composition, functions, and engineering. Curr. Opin. Biotechnol. 73, 135–142 (2021).

    Article  Google Scholar 

  14. Liu, H., Brettell, L. E. & Singh, B. Linking the phyllosphere microbiome to plant health. Trends Plant Sci. 25, 841–844 (2020).

    Article  CAS  Google Scholar 

  15. Vorholt, J. A. Microbial life in the phyllosphere. Nat. Rev. Microbiol. 10, 828–840 (2012).

    Article  CAS  Google Scholar 

  16. Liu, H., Brettell, L. E., Qiu, Z. & Singh, B. K. Microbiome-mediated stress resistance in plants. Trends Plant Sci. 25, 733–743 (2020).

    Article  CAS  Google Scholar 

  17. Xu, P. et al. Temporal metabolite responsiveness of microbiota in the tea plant phyllosphere promotes continuous suppression of fungal pathogens. J. Adv. Res. 39, 49–60 (2021).

    Article  Google Scholar 

  18. Wang, M. & Cernava, T. Overhauling the assessment of agrochemical-driven interferences with microbial communities for improved global ecosystem integrity. Environ. Sci. Ecotechnol. 4, 100061 (2020).

    Article  Google Scholar 

  19. Hegazi, N., Hartmann, A. & Ruppel, S. The plant microbiome: exploration of plant–microbe interactions for improving agricultural productivity. J. Adv. Res. 19, 1–2 (2019).

    Article  CAS  Google Scholar 

  20. Mittelviefhaus, M., Muller, D. B., Zambelli, T. & Vorholt, J. A. A modular atomic force microscopy approach reveals a large range of hydrophobic adhesion forces among bacterial members of the leaf microbiota. ISME J. 13, 1878–1882 (2019).

    Article  CAS  Google Scholar 

  21. Sapkota, R., Knorr, K., Jorgensen, L. N., O’Hanlon, K. A. & Nicolaisen, M. Host genotype is an important determinant of the cereal phyllosphere mycobiome. New Phytol. 207, 1134–1144 (2015).

    Article  CAS  Google Scholar 

  22. Bodenhausen, N., Bortfeld-Miller, M., Ackermann, M. & Vorholt, J. A. A synthetic community approach reveals plant genotypes affecting the phyllosphere microbiota. PLoS Genet. 10, e1004283 (2014).

    Article  Google Scholar 

  23. Horton, M. W. et al. Genome-wide association study of Arabidopsis thaliana leaf microbial community. Nat. Commun. 5, 5320 (2014).

    Article  ADS  Google Scholar 

  24. Wagner, M. R. et al. Host genotype and age shape the leaf and root microbiomes of a wild perennial plant. Nat. Commun. 7, 12151 (2016).

    Article  ADS  CAS  Google Scholar 

  25. Shakir, S., Zaidi, S. S., de Vries, F. T. & Mansoor, S. Plant genetic networks shaping phyllosphere microbial community. Trends Genet. 37, 306–316 (2021).

    Article  CAS  Google Scholar 

  26. Xiong, C. et al. Plant developmental stage drives the differentiation in ecological role of the maize microbiome. Microbiome 9, 171 (2021).

    Article  CAS  Google Scholar 

  27. Laforest-Lapointe, I., Paquette, A., Messier, C. & Kembel, S. W. Leaf bacterial diversity mediates plant diversity and ecosystem function relationships. Nature 546, 145–147 (2017).

    Article  ADS  CAS  Google Scholar 

  28. Chen, T. et al. A plant genetic network for preventing dysbiosis in the phyllosphere. Nature 580, 653–657 (2020).

    Article  ADS  CAS  Google Scholar 

  29. Pang, Z. et al. Linking plant secondary metabolites and plant microbiomes: a review. Front. Plant Sci. 12, 621276 (2021).

    Article  Google Scholar 

  30. Pfeilmeier, S. et al. The plant NADPH oxidase RBOHD is required for microbiota homeostasis in leaves. Nat. Microbiol. 6, 852–864 (2021).

    Article  CAS  Google Scholar 

  31. Gupta, R. et al. Cytokinin drives assembly of the phyllosphere microbiome and promotes disease resistance through structural and chemical cues. ISME J. 16, 122–137 (2022).

    Article  CAS  Google Scholar 

  32. Massoni, J. et al. Consistent host and organ occupancy of phyllosphere bacteria in a community of wild herbaceous plant species. ISME J. 14, 245–258 (2020).

    Article  CAS  Google Scholar 

  33. Agler, M. T. et al. Microbial hub taxa link host and abiotic factors to plant microbiome variation. PLoS Biol. 14, e1002352 (2016).

    Article  Google Scholar 

  34. Ren, G. et al. Response of soil, leaf endosphere and phyllosphere bacterial communities to elevated CO2 and soil temperature in a rice paddy. Plant Soil 392, 27–44 (2015).

    Article  CAS  Google Scholar 

  35. Meyer, K.M. et al. Plant neighborhood shapes diversity and reduces interspecific variation of the phyllosphere microbiome. ISME J. 16, 1376–1387 (2022).

    Article  Google Scholar 

  36. Qiu, Y. et al. Warming and elevated ozone induce tradeoffs between fine roots and mycorrhizal fungi and stimulate organic carbon decomposition. Sci. Adv. 7, eabe9256 (2021).

    Article  ADS  CAS  Google Scholar 

  37. Yu, H., Zhang, Y. & Tan, W. The “neighbor avoidance effect” of microplastics on bacterial and fungal diversity and communities in different soil horizons. Environ. Sci. Ecotechnol. 8, 100121 (2021).

    Article  CAS  Google Scholar 

  38. Wang, Q. et al. Interactive effects of ozone exposure and nitrogen addition on the rhizosphere bacterial community of poplar saplings. Sci. Total Environ. 754, 142134 (2021).

    Article  ADS  CAS  Google Scholar 

  39. Zhang, H., Jiang, Q., Wang, J., Li, K. & Wang, F. Analysis on the impact of two winter precipitation episodes on PM2.5 in Beijing. Environ. Sci. Ecotechnol. 5, 100080 (2021).

    Article  CAS  Google Scholar 

  40. Feng, Z. et al. Ozone pollution threatens the production of major staple crops in East Asia. Nat. Food 3, 47–56 (2022).

    Article  CAS  Google Scholar 

  41. Zhu, Y. G. et al. Impacts of global change on the phyllosphere microbiome. New Phytol. 234, 1977–1986 (2021).

    Article  Google Scholar 

  42. Sawada, H. et al. Elevated ozone deteriorates grain quality of japonica rice cv. Koshihikari, even if it does not cause yield reduction. Rice 9, 7 (2016).

    Article  Google Scholar 

  43. Agathokleous, E. et al. Ozone affects plant, insect, and soil microbial communities: a threat to terrestrial ecosystems and biodiversity. Sci. Adv. 6, eabc1176 (2020).

    Article  ADS  CAS  Google Scholar 

  44. Mieczan, T. & Bartkowska, A. The effect of experimentally simulated climate warming on the microbiome of carnivorous plants—a microcosm experiment. Glob. Ecol. Conserv. 34, e02040 (2022).

    Article  Google Scholar 

  45. Liu, H. et al. Evidence for the plant recruitment of beneficial microbes to suppress soil-borne pathogens. New Phytol. 229, 2873–2885 (2021).

    Article  CAS  Google Scholar 

  46. Gao, M. et al. Disease-induced changes in plant microbiome assembly and functional adaptation. Microbiome 9, 187 (2021).

    Article  CAS  Google Scholar 

  47. Snelders, N. C. et al. Microbiome manipulation by a soil-borne fungal plant pathogen using effector proteins. Nat. Plants 6, 1365–1374 (2020).

    Article  CAS  Google Scholar 

  48. Humphrey, P. T. & Whiteman, N. K. Insect herbivory reshapes a native leaf microbiome. Nat. Ecol. Evol. 4, 221–229 (2020).

    Article  Google Scholar 

  49. Laforest-Lapointe, I., Messier, C. & Kembel, S. W. Tree leaf bacterial community structure and diversity differ along a gradient of urban intensity. mSystems 2, e00087–17 (2017).

    Article  Google Scholar 

  50. Imperato, V. et al. Characterisation of the Carpinus betulus L. phyllomicrobiome in urban and forest areas. Front. Microbiol. 10, 1110 (2019).

    Article  Google Scholar 

  51. Perreault, R. & Laforest-Lapointe, I. Plant–microbe interactions in the phyllosphere: facing challenges of the anthropocene. ISME J. 16, 339–345 (2021).

    Article  Google Scholar 

  52. Jain, A., Ranjan, S., Dasgupta, N. & Ramalingam, C. Nanomaterials in food and agriculture: an overview on their safety concerns and regulatory issues. Crit. Rev. Food Sci. Nutr. 58, 297–317 (2018).

    Article  CAS  Google Scholar 

  53. Sillen, W. M. A. et al. Nanoparticle treatment of maize analyzed through the metatranscriptome: compromised nitrogen cycling, possible phytopathogen selection, and plant hormesis. Microbiome 8, 127 (2020).

    Article  CAS  Google Scholar 

  54. Berg, G. & Cernava, T. The plant microbiota signature of the Anthropocene as a challenge for microbiome research. Microbiome 10, 54 (2022).

    Article  Google Scholar 

  55. Fan, X. et al. Microenvironmental interplay predominated by beneficial Aspergillus abates fungal pathogen incidence in paddy environment. Environ. Sci. Technol. 53, 13042–13052 (2019).

    Article  ADS  CAS  Google Scholar 

  56. Chen, Y. et al. Wheat microbiome bacteria can reduce virulence of a plant pathogenic fungus by altering histone acetylation. Nat. Commun. 9, 3429 (2018).

    Article  ADS  Google Scholar 

  57. Wang, M., Hashimoto, M. & Hashidoko, Y. Repression of tropolone production and induction of a Burkholderia plantarii pseudo-biofilm by carot-4-en-9,10-diol, a cell-to-cell signaling disrupter produced by Trichoderma virens. PLoS ONE 8, e78024 (2013).

    Article  ADS  CAS  Google Scholar 

  58. Bauermeister, A., Mannochio-Russo, H., Costa-Lotufo, L. V., Jarmusch, A. K. & Dorrestein, P. C. Mass spectrometry-based metabolomics in microbiome investigations. Nat. Rev. Microbiol. 20, 143–160 (2022).

    Article  CAS  Google Scholar 

  59. Matsumoto, H. et al. Reprogramming of phytopathogen transcriptome by a non-bactericidal pesticide residue alleviates its virulence in rice. Fundam. Res. 2, 198–207 (2022).

    Article  CAS  Google Scholar 

  60. Hou, S. et al. A microbiota–root–shoot circuit favours Arabidopsis growth over defence under suboptimal light. Nat. Plants 7, 1078–1092 (2021).

  61. Mathur, M., Nair, A. & Kadoo, N. Plant–pathogen interactions: microRNA-mediated trans-kingdom gene regulation in fungi and their host plants. Genomics 112, 3021–3035 (2020).

    Article  CAS  Google Scholar 

  62. Kaur, C. et al. Microbial methylglyoxal metabolism contributes towards growth promotion and stress tolerance in plants. Environ. Microbiol. 24, 2817–2836 (2021).

    Article  Google Scholar 

  63. Castrillo, G. et al. Root microbiota drive direct integration of phosphate stress and immunity. Nature 543, 513–518 (2017).

    Article  ADS  CAS  Google Scholar 

  64. Korenblum, E. et al. Rhizosphere microbiome mediates systemic root metabolite exudation by root-to-root signaling. Proc. Natl Acad. Sci. USA 117, 3874–3883 (2020).

    Article  ADS  CAS  Google Scholar 

  65. Chisholm, S. T., Coaker, G., Day, B. & Staskawicz, B. J. Host–microbe interactions: shaping the evolution of the plant immune response. Cell 124, 803–814 (2006).

    Article  CAS  Google Scholar 

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

    Article  ADS  CAS  Google Scholar 

  67. Bai, Y. et al. Functional overlap of the Arabidopsis leaf and root microbiota. Nature 528, 364–369 (2015).

    Article  ADS  CAS  Google Scholar 

  68. Vogel, C., Bodenhausen, N., Gruissem, W. & Vorholt, J. A. The Arabidopsis leaf transcriptome reveals distinct but also overlapping responses to colonization by phyllosphere commensals and pathogen infection with impact on plant health. New Phytol. 212, 192–207 (2016).

    Article  CAS  Google Scholar 

  69. Dodds, P. N. & Rathjen, J. P. Plant immunity: towards an integrated view of plant–pathogen interactions. Nat. Rev. Genet. 11, 539–548 (2010).

    Article  CAS  Google Scholar 

  70. Stringlis, I. A. et al. Root transcriptional dynamics induced by beneficial rhizobacteria and microbial immune elicitors reveal signatures of adaptation to mutualists. Plant J. 93, 166–180 (2018).

    Article  CAS  Google Scholar 

  71. He, J. et al. A LysM receptor heteromer mediates perception of arbuscular mycorrhizal symbiotic signal in rice. Mol. Plant 12, 1561–1576 (2019).

    Article  CAS  Google Scholar 

  72. Bozsoki, Z. et al. Ligand-recognizing motifs in plant LysM receptors are major determinants of specificity. Plant Sci. 369, 663–670 (2020).

    CAS  Google Scholar 

  73. Stringlis, I. A., Zhang, H., Pieterse, C. M. J., Bolton, M. D. & de Jonge, R. Microbial small molecules—weapons of plant subversion. Nat. Prod. Rep. 35, 410–433 (2018).

    Article  CAS  Google Scholar 

  74. Kong, H. G., Song, G. C., Sim, H. J. & Ryu, C. M. Achieving similar root microbiota composition in neighbouring plants through airborne signalling. ISME J. 15, 397–408 (2021).

    Article  CAS  Google Scholar 

  75. Vacher, C. et al. The phyllosphere: microbial jungle at the plant–climate interface. Annu. Rev. Ecol. Evol. Syst. 47, 1–24 (2016).

    Article  Google Scholar 

  76. Thapa, S. & Prasanna, R. Prospecting the characteristics and significance of the phyllosphere microbiome. Ann. Microbiol. 68, 229–245 (2018).

    Article  CAS  Google Scholar 

  77. Vorholt, J. A., Vogel, C., Carlstrom, C. I. & Muller, D. B. Establishing causality: opportunities of synthetic communities for plant microbiome research. Cell Host Microbe 22, 142–155 (2017).

    Article  CAS  Google Scholar 

  78. Chen, X., Wicaksono, W. A., Berg, G. & Cernava, T. Bacterial communities in the plant phyllosphere harbour distinct responders to a broad-spectrum pesticide. Sci. Total Environ. 751, 141799 (2021).

    Article  ADS  CAS  Google Scholar 

  79. Liu, Y. X. et al. A practical guide to amplicon and metagenomic analysis of microbiome data. Protein Cell 12, 315–330 (2021).

    Article  Google Scholar 

  80. Hosokawa, M. et al. Droplet-based microfluidics for high-throughput screening of a metagenomic library for isolation of microbial enzymes. Biosens. Bioelectron. 67, 379–385 (2015).

    Article  CAS  Google Scholar 

  81. Kehe, J. et al. Massively parallel screening of synthetic microbial communities. Proc. Natl Acad. Sci. USA 116, 12804–12809 (2019).

    Article  ADS  CAS  Google Scholar 

  82. Zhang, J. et al. High-throughput cultivation and identification of bacteria from the plant root microbiota. Nat. Protoc. 16, 988–1012 (2021).

    Article  CAS  Google Scholar 

  83. Grosskopf, T. & Soyer, O. S. Synthetic microbial communities. Curr. Opin. Microbiol. 18, 72–77 (2014).

    Article  CAS  Google Scholar 

  84. Vogel, C. M., Potthoff, D. B., Schafer, M., Barandun, N. & Vorholt, J. A. Protective role of the Arabidopsis leaf microbiota against a bacterial pathogen. Nat. Microbiol. 6, 1537–1548 (2021).

    Article  CAS  Google Scholar 

  85. Finkel, O. M. et al. A single bacterial genus maintains root growth in a complex microbiome. Nature 587, 103–108 (2020).

  86. Wagner, M. R. et al. Microbe-dependent heterosis in maize. Proc. Natl Acad. Sci. USA 118, e2021965118 (2021).

    Article  CAS  Google Scholar 

  87. Schafer, M., Vogel, C. M., Bortfeld-Miller, M., Mittelviefhaus, M. & Vorholt, J. A. Mapping phyllosphere microbiota interactions in planta to establish genotype–phenotype relationships. Nat. Microbiol. 7, 856–867 (2022).

    Article  CAS  Google Scholar 

  88. Han, B. & Huang, X. Sequencing-based genome-wide association study in rice. Curr. Opin. Plant Biol. 16, 133–138 (2013).

    Article  CAS  Google Scholar 

  89. Roman-Reyna, V. et al. The rice leaf microbiome has a conserved community structure controlled by complex host-microbe interactions. Cell Host Microbe https://doi.org/10.2139/ssrn.3382544 (2019).

  90. Deng, S. et al. Genome wide association study reveals plant loci controlling heritability of the rhizosphere microbiome. ISME J. 15, 3181–3194 (2021).

    Article  CAS  Google Scholar 

  91. Wagner, M. R., Busby, P. E. & Balint-Kurti, P. Analysis of leaf microbiome composition of near-isogenic maize lines differing in broad-spectrum disease resistance. New Phytol. 225, 2152–2165 (2020).

    Article  CAS  Google Scholar 

  92. Wagner, M. R., Roberts, J. H., Balint-Kurti, P. & Holland, J. B. Heterosis of leaf and rhizosphere microbiomes in field-grown maize. New Phytol. 228, 1055–1069 (2020).

    Article  CAS  Google Scholar 

  93. Nobori, T. et al. Transcriptome landscape of a bacterial pathogen under plant immunity. Proc. Natl Acad. Sci. USA 115, E3055–E3064 (2018).

    Article  CAS  Google Scholar 

  94. Xu, L. et al. Holo-omics for deciphering plant–microbiome interactions. Microbiome 9, 69 (2021).

    Article  Google Scholar 

  95. French, E., Kaplan, I., Iyer-Pascuzzi, A., Nakatsu, C. H. & Enders, L. Emerging strategies for precision microbiome management in diverse agroecosystems. Nat. Plants 7, 256–267 (2021).

    Article  Google Scholar 

  96. Lemmon, Z. H. et al. Rapid improvement of domestication traits in an orphan crop by genome editing. Nat. Plants 4, 766–770 (2018).

    Article  CAS  Google Scholar 

  97. Kamilaris, A. & Prenafeta-Boldú, F. X. Deep learning in agriculture: a survey. Comput. Electron. Agric. 147, 70–90 (2018).

    Article  Google Scholar 

  98. Zhou, L., Zhang, C., Liu, F., Qiu, Z. & He, Y. Application of deep learning in food: a review. Compr. Rev. Food Sci. Food Saf. 18, 1793–1811 (2019).

    Article  Google Scholar 

  99. Moreno-Indias, I. et al. Statistical and machine learning techniques in human microbiome studies: contemporary challenges and solutions. Front. Microbiol. 12, 635781 (2021).

    Article  Google Scholar 

  100. Song, P., Wang, J., Guo, X., Yang, W. & Zhao, C. High-throughput phenotyping: breaking through the bottleneck in future crop breeding. Crop J. 9, 633–645 (2021).

    Article  Google Scholar 

Download references

Acknowledgements

This study was supported by National Key R&D Program of China (2021YFE0113700), National Natural Science Foundation of China (32122074, U21A20219) and Strategic Research on ‘Plant Microbiome and Agroecosystem Health’ (2020ZL008, Cao Guangbiao High Science and Technology Foundation, Zhejiang University). Artwork was created in part using Figdraw (https://www.figdraw.com), and we also appreciate S. Chen (College of Biosystems Engineering and Food Science, Zhejiang University) for visualizing DL models.

Author information

Authors and Affiliations

  1. State Key Laboratory of Rice Biology & Ministry of Agricultural and Rural Affairs Laboratory of Molecular Biology of Crop Pathogens and Insects, Zhejiang University, Hangzhou, China

    Chengfang Zhan, Haruna Matsumoto & Mengcen Wang

  2. Key Laboratory of Biology of Crop Pathogens and Insects of Zhejiang Province, Institute of Pesticide and Environmental Toxicology, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China

    Chengfang Zhan, Haruna Matsumoto & Mengcen Wang

  3. College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China

    Yufei Liu

  4. Global Education Program for AgriScience Frontiers, Graduate School of Agriculture, Hokkaido University, Sapporo, Japan

    Mengcen Wang

Authors
  1. Chengfang Zhan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Haruna Matsumoto
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yufei Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mengcen Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

M.W., H.M. and C.Z. conceived the manuscript. M.W., C.Z. and H.M. wrote the manuscript. Y.L. provided critical suggestions and edited the section on deep learning.

Corresponding author

Correspondence to Mengcen Wang.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Food thanks Hongwei Liu, Yang Bai and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

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

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

Zhan, C., Matsumoto, H., Liu, Y. et al. Pathways to engineering the phyllosphere microbiome for sustainable crop production. Nat Food 3, 997–1004 (2022). https://doi.org/10.1038/s43016-022-00636-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s43016-022-00636-2

This article is cited by

Search

Advanced search

Quick links

Nature Briefing Microbiology

Sign up for the Nature Briefing: Microbiology newsletter — what matters in microbiology research, free to your inbox weekly.

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