Niche differentiation modulates metabolites abundance and composition in silicon fertilizer amended soil during sugarcane growth
Notice bibliographique
Résumé
BACKGROUND: As one of the vital crops globally, sugarcane (Saccharum officinarum L.) has been one of model crops for conducting metabolome research. Although many studies have focused on understanding bioactive components in specific sugarcane tissues, crucial questions have been left unanswered about the response of metabolites to niche differentiation such as different sugarcane tissues (leaf, stem and root), and soil regions (rhizosphere and bulk) under silicon (Si) amended soils. Here, nontargeted metabolite profiling method was leveraged to assess the similarities and differences in the abundance and community composition of metabolites in the different sugarcane and soil compartments. Identify the compartment-specific expression patterns of metabolites, and their association with cane agronomic traits and edaphic factors. We also investigated the response of sugarcane agronomic traits and edaphic factors to Si amended soil. RESULTS: We found that Si fertilizer exhibited the advantages of overwhelmingly promoting the height and theoretical production of cane, and profoundly increased soil Si content by 24.8 and 27.0%, while soil available potassium (AK) was enhanced by 3.07 and 2.67 folds in the bulk and rhizosphere soils, respectively. It was also noticed that available phosphorus (AP) in the rhizosphere soil tremendously increased by 105.5%. We detected 339 metabolites in 30 samples using LC-MS/MS analyses, 161 of which were classified and annotated, including organooxygen compounds (19.9%), carboxylic acids and derivatives (15.5%), fatty acyls (15.5%), flavonoids (4.4%), phenols (4.4%), and benzene and substituted derivatives (3.7%). In addition, the total percentages covered by these core metabolites in each compartment ranged from 94.0% (bulk soil) to 93.4% (rhizosphere soil), followed by 87.4% (leaf), 81.0% (root) and 80.5% (stem), suggesting that these bioactive compounds may have migrated from the belowground tissues and gradually filtered in various aboveground niches of the plant. We also observed that the variations and enrichment of metabolites abundance and community were compartment-specific. Furthermore, some key bioactive compounds were markedly associated with plant growth parameters and soil edaphic. CONCLUSION: Taken together, we hypothesized that Si utilization can exhibit the advantage of enhancing edaphic factors and cane agronomic traits, and variations in metabolites community are tissue-specific.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».