Analysis of metabolome and microbiome revealed the resistance mechanisms in sugarcane cultivars with high resistance to pokkah boeng disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Background Endophytes are reported to play a role in resistance against plant pathogens. Understanding the metabolite-mediated endophytic microbiota composition in plants provides insights to improve plant stress resistance. In this study, via metabolome and microbiome analyses, we aimed to elucidate the resistance mechanism of sugarcane cultivars with high resistance to sugarcane pokkah boeng disease (PBD). The endophytic microbial composition and metabolites in the stems of various sugarcane cultivars with high resistance (HR) or high susceptibility (HS) to PBD were analyzed. Results The results revealed that the endophytic fungi with biocontrol effects such as Shinella , Dechloromonas , and Microbacter were significantly enriched, and the abundance of pathogenic fungi such as Fusarium , Ramichloridium , Scleroramularia , Phaeosphaeriopsis , Sarocladium , Zygophiala , Gibberella , Pseudocercospora , Cyphellophora , Monocillium , Apiotrichum , Microsphaeropsis , and Scleroramularia significantly reduced in the stems of HR cultivars. Additionally, six metabolites [citric acid, isocitrate, malic acid, PC(16:0/0:0), phosphocholine, and lysoPC(16:0)] were significantly related to the endophytes in the stems of HR cultivars. Conclusions These results suggested that more abundance of antagonistic microbes and highly active metabolic functions of endophytes in the HR cultivars were the important mechanisms underlying their higher resistance to PBD. Graphical abstract
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it