Testosterone-inducible Regulator Is a Kinase That Drives Steroid Sensing and Metabolism in Comamonas testosteroni
Bibliographic record
Abstract
The mechanism of gene regulation by steroids in bacteria is still a mystery. We use steroid-inducible 3alpha-hydroxysteroid dehydrogenase/carbonyl reductase (3alpha-HSD/CR) as a reporter system to study steroid signaling in Comamonas testosteroni. In previous investigations we cloned and characterized the 3alpha-HSD/CR-encoding gene, hsdA. In addition, we identified two negative regulator genes (repA and repB) in the vicinity of hsdA, the protein products which repress hsdA expression on the level of transcription and translation, respectively. Recently, a positive regulator of hsdA expression, TeiR (testosterone-inducible regulator), was found by transposon mutagenesis, but the mode of its action remained obscure. In the present work we produced a TeiR-green fluorescent fusion protein and showed that TeiR is a membrane protein with asymmetrical localization at one of the cell poles of C. testosteroni. Knock-out mutants of the teiR gene revealed that TeiR provides swimming and twitching motility of C. testosteroni to the steroid substrate source. TeiR also mediated an induced expression of 3alpha-HSD/CR which was paralleled by an enhanced catabolism of testosterone. We also found that TeiR responds to a variety of different steroids other than testosterone. Biochemical analysis with several deletion mutants of the teiR gene revealed TeiR to consist of three different functional domains, an N-terminal domain important for membrane association, a central steroid binding site, and a C-terminal part mediating TeiR function. Finally, we could demonstrate that TeiR works as a kinase in the steroid signaling chain in C. testosteroni. Overall, we provide evidence that TeiR mediates steroid sensing and metabolism in C. testosteroni via its steroid binding and kinase activity.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".