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1.
Science ; 383(6689): 1318-1325, 2024 Mar 22.
Artículo en Inglés | MEDLINE | ID: mdl-38513014

RESUMEN

Plants are constantly exposed to volatile organic compounds (VOCs) that are released during plant-plant communication, within-plant self-signaling, and plant-microbe interactions. Therefore, understanding VOC perception and downstream signaling is vital for unraveling the mechanisms behind information exchange in plants, which remain largely unexplored. Using the hormone-like function of volatile terpenoids in reproductive organ development as a system with a visual marker for communication, we demonstrate that a petunia karrikin-insensitive receptor, PhKAI2ia, stereospecifically perceives the (-)-germacrene D signal, triggering a KAI2-mediated signaling cascade and affecting plant fitness. This study uncovers the role(s) of the intermediate clade of KAI2 receptors, illuminates the involvement of a KAI2ia-dependent signaling pathway in volatile communication, and provides new insights into plant olfaction and the long-standing question about the nature of potential endogenous KAI2 ligand(s).


Asunto(s)
Furanos , Hidrolasas , Petunia , Piranos , Compuestos Orgánicos Volátiles , Hidrolasas/genética , Hidrolasas/metabolismo , Transducción de Señal , Compuestos Orgánicos Volátiles/metabolismo , Petunia/fisiología , Furanos/metabolismo , Piranos/metabolismo , Sesquiterpenos de Germacrano/metabolismo
2.
Front Plant Sci ; 14: 1139274, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-36938050

RESUMEN

Type-VI glandular trichomes of wild tomato Solanum habrochaites PI127826 produce high levels of the sesquiterpene 7-epizingiberene and its derivatives, making the plant repellent and toxic to several pest insects and pathogens. How wild tomato trichomes achieve such high terpene production is still largely unknown. Here we show that a cross (F1) with a cultivated tomato produced only minute levels of 7-epizingiberene. In the F2-progeny, selected for the presence of the 7-epizingiberene biosynthesis genes, only three percent produced comparable amounts the wild parent, indicating this trait is recessive and multigenic. Moreover, trichome density alone did not explain the total levels of terpene levels found on the leaves. We selected F2 plants with the "high-production active-trichome phenotype" of PI127826, having trichomes producing about 150 times higher levels of terpenes than F2 individuals that displayed a "low-production lazy-trichome phenotype". Terpene quantities in trichomes of these F2 plants correlated with the volume of the storage cavity and shape of the gland. We found that trichome morphology is not a predetermined characteristic, but cavity volume rather depended on gland-cell metabolic activity. Inhibitor assays showed that the plastidial-precursor pathway (MEP) is fundamental for high-level production of both cytosolic as well as plastid-derived terpenes in tomato trichomes. Additionally, gene expression profiles of isolated secretory cells showed that key enzymes in the MEP pathway were higher expressed in active trichomes. We conclude that the MEP pathway is the primary precursor-supply route in wild tomato type-VI trichomes and that the high-production phenotype of the wild tomato trichome is indeed a multigenic trait.

3.
BMC Plant Biol ; 21(1): 315, 2021 Jul 02.
Artículo en Inglés | MEDLINE | ID: mdl-34215189

RESUMEN

BACKGROUND: Plant-produced specialised metabolites are a powerful part of a plant's first line of defence against herbivorous insects, bacteria and fungi. Wild ancestors of present-day cultivated tomato produce a plethora of acylsugars in their type-I/IV trichomes and volatiles in their type-VI trichomes that have a potential role in plant resistance against insects. However, metabolic profiles are often complex mixtures making identification of the functionally interesting metabolites challenging. Here, we aimed to identify specialised metabolites from a wide range of wild tomato genotypes that could explain resistance to vector insects whitefly (Bemisia tabaci) and Western flower thrips (Frankliniella occidentalis). We evaluated plant resistance, determined trichome density and obtained metabolite profiles of the glandular trichomes by LC-MS (acylsugars) and GC-MS (volatiles). Using a customised Random Forest learning algorithm, we determined the contribution of specific specialised metabolites to the resistance phenotypes observed. RESULTS: The selected wild tomato accessions showed different levels of resistance to both whiteflies and thrips. Accessions resistant to one insect can be susceptible to another. Glandular trichome density is not necessarily a good predictor for plant resistance although the density of type-I/IV trichomes, related to the production of acylsugars, appears to correlate with whitefly resistance. For type VI-trichomes, however, it seems resistance is determined by the specific content of the glands. There is a strong qualitative and quantitative variation in the metabolite profiles between different accessions, even when they are from the same species. Out of 76 acylsugars found, the random forest algorithm linked two acylsugars (S3:15 and S3:21) to whitefly resistance, but none to thrips resistance. Out of 86 volatiles detected, the sesquiterpene α-humulene was linked to whitefly susceptible accessions instead. The algorithm did not link any specific metabolite to resistance against thrips, but monoterpenes α-phellandrene, α-terpinene and ß-phellandrene/D-limonene were significantly associated with susceptible tomato accessions. CONCLUSIONS: Whiteflies and thrips are distinctly targeted by certain specialised metabolites found in wild tomatoes. The machine learning approach presented helped to identify features with efficacy toward the insect species studied. These acylsugar metabolites can be targets for breeding efforts towards the selection of insect-resistant cultivars.


Asunto(s)
Resistencia a la Enfermedad/genética , Variación Genética , Hemípteros/fisiología , Metaboloma/genética , Solanum/genética , Thysanoptera/fisiología , Tricomas/genética , Tricomas/metabolismo , Algoritmos , Animales , Ecotipo , Genotipo , Fenotipo , Compuestos Orgánicos Volátiles/análisis
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