Linking Plant Metabolomics with Fungal Functional Dynamics Reveals a Noncanonical S‐R‐C Adaptive Trajectory
Source abstract
Abstract
ABSTRACT Phyllosphere plant‐fungal interactions are crucial for crop health, yet how leaf metabolite dynamics interplay with fungal functional succession remains unclear. Using field‐based holo‐omics, we show that developmental shifts in sorghum leaf metabolomes drive a noncanonical temporal trajectory of fungal life‐history strategies from stress‐tolerator (S), through ruderal (R), to competitor (C). Young leaves deploy antifungal metabolites that select for stress‐tolerators (S‐strategists) with expanded genomes. A transient increase in maltose abundance during flowering promotes the proliferation of fast‐growing ruderal (R‐) strategists. As plants mature, competitive (C‐) strategists rely on secondary metabolism to persist in crowded communities. We further detect asynchrony between taxonomic and functional beta diversities, and a drop in the taxonomic one coincides with upregulated expression of fungal genes encoding secreted carbohydrate‐active enzymes and effectors. Collectively, these findings identify developmental stage‐specific leaf metabolomes as key determinants of phyllosphere fungal adaptation and functioning.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Plant-Microbe Interactions and Immunity · Mycorrhizal Fungi and Plant Interactions · Plant Gene Expression Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
State Key Laboratory of Microbial Diversity and Innovative Utilization Institute of Microbiology Chinese Academy of Sciences Beijing China
College of Life Sciences University of Chinese Academy of Sciences Beijing China
Department of Plant and Microbial Biology University of California Berkeley California USA
Funding
National Natural Science Foundation of China
References (89)
Show source-provided references
1. C. E.Morris “Phyllosphere ”IneLS (Ed.)(2001) https://doi.org/10.1038/npg.els.0000400.10.1038/npg.els.0000400 ↗
2. 10.1038/s41586‐020‐2185‐010.1038/s41586‐020‐2185‐0 ↗
3. 10.1016/j.tplants.2020.06.00310.1016/j.tplants.2020.06.003 ↗
4. 10.1146/annurev‐ecolsys‐121415‐03223810.1146/annurev‐ecolsys‐121415‐032238 ↗
5. 10.1038/nrmicro291010.1038/nrmicro2910 ↗
6. 10.1038/s41579‐018‐0116‐y10.1038/s41579‐018‐0116‐y ↗
7. 10.1038/nrmicro.2016.5910.1038/nrmicro.2016.59 ↗
8. 10.1038/s41467‐023‐44172‐410.1038/s41467‐023‐44172‐4 ↗
9. 10.1038/s41467‐019‐13913‐910.1038/s41467‐019‐13913‐9 ↗
10. 10.1111/j.1469‐8137.2010.03197.x10.1111/j.1469‐8137.2010.03197.x ↗
11. 10.1139/cjm‐2023‐021510.1139/cjm‐2023‐0215 ↗
12. 10.1093/hr/uhaf04210.1093/hr/uhaf042 ↗
13. 10.1016/j.tree.2018.04.01210.1016/j.tree.2018.04.012 ↗
14. 10.1016/j.tree.2023.01.00810.1016/j.tree.2023.01.008 ↗
15. 10.1038/250026a010.1038/250026a0 ↗
16. 10.1038/s41564‐023‐01465‐010.1038/s41564‐023‐01465‐0 ↗
17. 10.1038/s41467‐023‐43297‐w10.1038/s41467‐023‐43297‐w ↗
18. 10.1073/pnas.241303212210.1073/pnas.2413032122 ↗
19. 10.1038/ismej.2015.19110.1038/ismej.2015.191 ↗
20. 10.1038/s41396‐019‐0510‐010.1038/s41396‐019‐0510‐0 ↗
21. 10.1038/s41564‐024‐01687‐w10.1038/s41564‐024‐01687‐w ↗
22. 10.1111/ele.1422410.1111/ele.14224 ↗
23. 10.1128/microbiolspec.FUNK‐0057‐201610.1128/microbiolspec.FUNK‐0057‐2016 ↗
24. 10.1073/pnas.211885211910.1073/pnas.2118852119 ↗
25. 10.1038/s41396‐018‐0342‐310.1038/s41396‐018‐0342‐3 ↗
26. 10.1038/s41396‐020‐0606‐610.1038/s41396‐020‐0606‐6 ↗
27. 10.1371/journal.pgen.100428310.1371/journal.pgen.1004283 ↗
28. 10.1139/cjb‐2013‐019410.1139/cjb‐2013‐0194 ↗
29. 10.1038/ismej.2010.910.1038/ismej.2010.9 ↗
30. 10.1186/s40168‐016‐0174‐110.1186/s40168‐016‐0174‐1 ↗
31. 10.1038/s41396‐021‐01184‐610.1038/s41396‐021‐01184‐6 ↗
32. 10.1016/j.funeco.2018.10.00110.1016/j.funeco.2018.10.001 ↗
33. 10.1111/nph.1341810.1111/nph.13418 ↗
34. 10.1093/jxb/eraa42410.1093/jxb/eraa424 ↗
35. 10.1126/science.adv667510.1126/science.adv6675 ↗
36. 10.1126/science.adf512110.1126/science.adf5121 ↗
37. 10.48130/bpr‐0025‐000210.48130/bpr‐0025‐0002 ↗
38. 10.1111/gcb.7020710.1111/gcb.70207 ↗
39. 10.1073/pnas.190750011610.1073/pnas.1907500116 ↗
40. 10.1111/mec.1634310.1111/mec.16343 ↗
41. 10.1038/s41396‐018‐0264‐010.1038/s41396‐018‐0264‐0 ↗
42. How Populations Grow: The Exponential and Logistic Equations
43. 10.1007/s13225‐020‐00466‐210.1007/s13225‐020‐00466‐2 ↗
44. 10.1094/mpmi‐09‐23‐0142‐fi10.1094/mpmi‐09‐23‐0142‐fi ↗
45. 10.1146/annurev‐phyto‐102313‐04583110.1146/annurev‐phyto‐102313‐045831 ↗
46. 10.3389/fpls.2022.85310610.3389/fpls.2022.853106 ↗
47. 10.1016/j.pestbp.2017.05.01210.1016/j.pestbp.2017.05.012 ↗
48. 10.1016/j.bmcl.2014.02.00510.1016/j.bmcl.2014.02.005 ↗
49. 10.3390/plants1408124410.3390/plants14081244 ↗
50. 10.1111/nph.7015510.1111/nph.70155 ↗
51. 10.1038/s41564‐023‐01379‐x10.1038/s41564‐023‐01379‐x ↗
52. 10.1007/s11368‐022‐03394‐710.1007/s11368‐022‐03394‐7 ↗
53. 10.1002/mbo3.35510.1002/mbo3.355 ↗
54. 10.1111/1365‐2435.1362410.1111/1365‐2435.13624 ↗
55. 10.1111/pce.1367210.1111/pce.13672 ↗
56. 10.3389/fpls.2023.127874510.3389/fpls.2023.1278745 ↗
57. H.Zhu K.Fazliddin Q.Li et al. “Contrasting Adaptations of Soil Prokaryotes and Arbuscular Mycorrhizal Fungi in Saline Wildland and Non‐Saline Farmland ”Fundamental Research(2025) (In Press) https://doi.org/10.1016/j.fmre.2025.02.009.10.1016/j.fmre.2025.02.009 ↗
58. 10.1038/s41467‐025‐60390‐410.1038/s41467‐025‐60390‐4 ↗
59. 10.1038/s41467‐024‐53753‐w10.1038/s41467‐024‐53753‐w ↗
60. 10.1016/j.chom.2025.02.00210.1016/j.chom.2025.02.002 ↗
61. 10.1098/rstb.2011.006310.1098/rstb.2011.0063 ↗
62. 10.1111/oik.0149310.1111/oik.01493 ↗
63. 10.1128/mmbr.00002‐1710.1128/mmbr.00002‐17 ↗
64. 10.1128/mmbr.00051‐1210.1128/mmbr.00051‐12 ↗
65. 10.1007/s13225‐025‐00559‐w10.1007/s13225‐025‐00559‐w ↗
66. 10.1016/j.catena.2020.10509910.1016/j.catena.2020.105099 ↗
67. 10.1111/nph.1792810.1111/nph.17928 ↗
68. 10.1038/s41396‐018‐0076‐210.1038/s41396‐018‐0076‐2 ↗
69. 10.1073/pnas.171730811510.1073/pnas.1717308115 ↗
70. 10.1093/bioinformatics/bty56010.1093/bioinformatics/bty560 ↗
71. 10.1038/nmeth.192310.1038/nmeth.1923 ↗
72. 10.1093/nar/gkac11210.1093/nar/gkac112 ↗
73. 10.1093/bioinformatics/btv03310.1093/bioinformatics/btv033 ↗
74. 10.1101/gr.228429.11710.1101/gr.228429.117 ↗
75. 10.1093/bioinformatics/bts56510.1093/bioinformatics/bts565 ↗
76. 10.1038/nmeth.419710.1038/nmeth.4197 ↗
77. 10.1093/nar/gky108510.1093/nar/gky1085 ↗
78. 10.1038/nmeth.317610.1038/nmeth.3176 ↗
79. 10.1038/s41587‐021‐01156‐310.1038/s41587‐021‐01156‐3 ↗
80. 10.1094/MPMI‐08‐21‐0201‐R10.1094/MPMI‐08‐21‐0201‐R ↗
81. G. L.Simpson P.Solymos M.Stevens andH. J.Wagner "Vegan: Community Ecology Package "R package version(2018)..
82. 10.1128/msystems.00745‐2210.1128/msystems.00745‐22 ↗
83. Psych: Procedures for Personality and Psychological Research
84. 10.1007/978-3-319-24277-410.1007/978-3-319-24277-4 ↗
85. 10.1093/nar/gkae25310.1093/nar/gkae253 ↗
86. 10.1093/bioinformatics/bty63310.1093/bioinformatics/bty633 ↗
87. 10.18637/jss.v022.i0710.18637/jss.v022.i07 ↗
88. 10.18637/jss.v086.i0110.18637/jss.v086.i01 ↗
89. 10.1111/j.2041‐210X.2009.00007.x10.1111/j.2041‐210X.2009.00007.x ↗