Control of pyrimidine formation in<i>Pseudomonas</i><i>putida</i>ATCC 17536
Bibliographic record
Abstract
The regulation of de novo pyrimidine biosynthesis in Pseudomonas putida ATCC 17536 by pyrimidines was explored. The pathway enzyme activities were higher in glucose-grown cells than in succinate-grown cells, indicating catabolite repression by succinate. In P. putida cells grown on succinate as a carbon source, only aspartate transcarbamoylase activity was greatly diminished by uracil supplementation. When glucose was the carbon source, orotic acid supplementation significantly decreased orotate phosphoribosyltransferase and orotidine 5'-monophosphate (OMP) decarboxylase activities. Uracil auxotrophs, deficient for dihydroorotase activity or with reduced phosphoribosyltransferase activity, were isolated. After pyrimidine limitation of both auxotrophs, the greatest derepression of enzyme activity was observed for OMP decarboxylase independent of carbon source. Orotic acid induced both phosphoribosyltransferase and decarboxylase activities in glucose-grown cells of the dihydroorotase-deficient strain. Regulation at the transcriptional level of de novo pyrimidine biosynthetic enzyme synthesis in P. putida ATCC 17536 was observed, which contrasts with previous observations.
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".