Altered Metabolism in Knockdown Lines of Two HXXXD/BAHD Acyltransferases During Wound Healing in Potato Tubers
Bibliographic record
Abstract
Suberin biosynthesis involves the coordinated regulation of both phenolic and aliphatic metabolisms. HXXXD/BAHD acyltransferases occupy a unique place in suberization, as they function to crosslink phenolic and aliphatic monomers during suberin assembly. To date, only one suberin-associated HXXXD/BAHD acyltransferase, StFHT, has been described in potatoes, whereas, in Arabidopsis, at least two are implicated in suberin biosynthesis. RNAseq data from wound-induced potato tubers undergoing suberization indicate that transcripts for 28 HXXXD/BAHD acyltransferase genes accumulate in response to wounding. In the present study, we generated RNAi knockdown lines for StFHT and another highly wound-induced HXXXD/BAHD acyltransferase, designated StHCT, and characterized their wound-induced suberin phenotype. StFHT-RNAi and StHCT-RNAi knockdown lines share the same aliphatic suberin phenotype of reduced esterified ferulic acid and ferulates, which is similar to the previously described StFHT-RNAi knockdown suberin phenotype. However, the phenolic suberin phenotype differed between the two knockdown genotypes, with StHCT-RNAi knockdown lines having proportionately more p-hydroxyphenyl-derived moieties than either StFHT-RNAi knockdown or empty vector control lines. Analysis of soluble polar metabolites revealed that StHCT catalyzes a step upstream from StFHT. Overall, our data support the involvement of more than one HXXXD/BAHD acyltransferase in potato suberin biosynthesis.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".