Peroxysomal Carnitine Acetyl Transferase Influences Host Colonization Capacity in <i>Sclerotinia sclerotiorum</i>
Bibliographic record
Abstract
In lower eukaryotes, the glyoxylate cycle allows cells to utilize two-carbon compounds when simple sugars are not available. In filamentous fungi, glyoxylate metabolism is coupled with β-oxidation of fatty acids, and both are localized to ubiquitous eukaryotic organelles called peroxisomes. Acetyl coenzyme A (acetyl-CoA) produced during β-oxidation is transported via the cytosol into mitochondria for further metabolism. A peroxisomal-specific pathway for acetyl-CoA transport requiring peroxisomal carnitine acetyl transferase (CAT) activity has been identified in Magnaporthe grisea peroxisomes. Here, we report that a Sclerotinia sclerotiorum ortholog of the M. grisea peroxisomal CAT-encoding gene Pth2 (herein designated Ss-pth2) is required for virulence-associated host colonization. Null (ss-pth2) mutants, obtained by in vitro transposon mutagenesis, failed to utilize fatty acids, acetate, or glycerol as sole carbon sources for growth. Gene expression analysis of these mutants showed altered levels of transcript accumulation for glyoxylate cycle enzymes. Ss-pth2 disruption also affected sclerotial, apothecial, and appressorial development and morphology, as well as oxalic acid accumulation when cultured with acetate or oleic acid as sole carbon nutrient sources. Although mutants were able to penetrate and initially colonize host tissue, subsequent colonization was impaired. Genetic complementation with the wild-type Ss-pth2 restored wild-type virulence phenotypes. These findings suggest an essential role in S. sclerotiorum for the peroxisomal metabolic pathways for oxalic acid synthesis and host colonization.
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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 | 0.001 |
| 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".