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Legume-specific recruitment of rhizobia by hyphae of arbuscular mycorrhizal fungi

Summary

Underground fungal networks connect different legume plants and act like sophisticated GPS systems for helpful bacteria. These fungi transport chemical signals (flavonoids) from plant roots along their hyphae, guiding specific types of nitrogen-fixing bacteria to their correct host plants. This discovery shows how fungi help bacteria find the right plants to form symbiotic partnerships, improving natural nitrogen fixation and potentially reducing the need for chemical fertilizers in agriculture.

Background

Legume-rhizobia symbiosis is crucial for sustainable agriculture through nitrogen fixation. Rhizobia typically recognize host legumes through flavonoids released by roots over short distances (millimeters). Recent research demonstrates that arbuscular mycorrhizal fungi can extend this recognition beyond 15 cm by transporting flavonoids along their hyphae.

Objective

To investigate whether common mycorrhizal networks (CMNs) linking different legume species can transmit host-specific signals to guide rhizobia toward their appropriate hosts. The study hypothesized that CMNs function as a navigation system using chemical signals to orient rhizobia toward compatible host plants.

Results

S. meliloti preferentially migrated toward M. truncatula (155±8 nodules in vitro, 71-82 in greenhouse), while B. diazoefficiens migrated toward G. max (13±3 in vitro, 15-18 in greenhouse). M. truncatula-connected hyphae released DL-liquiritigenin, naringenin, sakuranetin, and 3,7-dimethylquercetin, while G. max-connected hyphae released daidzin, 6″-O-malonyldaidzin, irilone, and erylatissin A.

Conclusion

CMNs function as a sophisticated navigation system using host-specific flavonoid signals to guide rhizobia toward compatible hosts, improving nodulation efficiency. These findings demonstrate the dual role of AM fungal hyphae as physical highways and chemical signal carriers, with applications for sustainable agriculture and nitrogen fixation optimization.
  • Published in:ISME Journal,
  • Study Type:Experimental Study,
  • Source: 40396656
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