Regulation of the <scp>KstR</scp>2 regulon of <i><scp>M</scp>ycobacterium tuberculosis</i> by a cholesterol catabolite
Bibliographic record
Abstract
Cholesterol catabolism is widespread in actinobacteria and is critical for Mycobacterium tuberculosis (Mtb) virulence. Catabolism of steroid nucleus rings C and D is poorly understood: it is initiated by the CoA thioesterification of 3aα-H-4α(3'-propanoate)-7aβ-methylhexahydro-1,5-indanedione (HIP) by FadD3, whose gene is part of the KstR2 regulon. In Mtb, genes of this regulon were upregulated up to 30- and 22-fold during growth on cholesterol and HIP, respectively, versus another minimal medium. In contrast, genes involved in degrading the cholesterol side-chain and nucleus rings A and B were only upregulated during growth on cholesterol. Similar results were obtained in Rhodococcus jostii RHA1. Moreover, the regulon was not upregulated in a ΔfadD3 mutant unable to produce HIP-CoA. In electrophoretic mobility shift assays, HIP-CoA relieved the binding of KstR2(Mtb) to each of three KstR2 boxes: CoASH, HIP and a related CoA thioester did not. Inspection of the structure of KstR2(RHA1) revealed no obvious HIP-CoA binding pocket. The results establish that Mtb can catabolize the entire cholesterol molecule and that HIP-CoA is an effector of KstR2. They further indicate that KstR2 specifically represses the expression of the HIP degradation genes in actinobacteria, which encode a lower pathway involved in the catabolism of multiple steroids.
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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".