PEX11β induces peroxisomal gene expression and alters peroxisome number during early Xenopus laevis development
Bibliographic record
Abstract
BACKGROUND: Peroxisomes are organelles whose roles in fatty acid metabolism and reactive oxygen species elimination have contributed much attention in understanding their origin and biogenesis. Many studies have shown that de novo peroxisome biogenesis is an important regulatory process, while yeast studies suggest that total peroxisome numbers are in part regulated by proteins such as Pex11, which can facilitate the division of existing peroxisomes. Although de novo biogenesis and divisions are likely important mechanisms, the regulation of peroxisome numbers during embryonic development is poorly understood. Peroxisome number and function are particularly crucial in oviparous animals such as frogs where large embryonic yolk and fatty acid stores must be quickly metabolized, and resulting reactive oxygen species eliminated. Here we elucidate the role of Pex11β in regulating peroxisomal gene expression and number in Xenopus laevis embryogenesis. RESULTS: Microinjecting haemagglutinin (HA) tagged Pex11β in early embryos resulted in increased RNA levels for peroxisome related genes PMP70 and catalase at developmental stages 10 and 20, versus uninjected embryos. Catalase and PMP70 proteins were found in punctate structures at stage 20 in control embryos, whereas the injection of ectopic HA-Pex11β induced their earlier localization in punctate structures at stage 10. Furthermore, the peroxisomal marker GFP-SKL, which was found localized as peroxisome-like structures at stage 20, was similarly found at stage 10 when co-microinjected with HA-Pex11β. CONCLUSIONS: Overexpressed Pex11β altered peroxisomal gene levels and induced the early formation of peroxisomes-like structures during development, both of which demonstrate that Pex11β may be a key regulator of peroxisome number in early Xenopus embryos.
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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) | 0.003 | 0.001 |
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".