Studies of a Ring-Cleaving Dioxygenase Illuminate the Role of Cholesterol Metabolism in the Pathogenesis of Mycobacterium tuberculosis
Bibliographic record
Abstract
Mycobacterium tuberculosis, the etiological agent of TB, possesses a cholesterol catabolic pathway implicated in pathogenesis. This pathway includes an iron-dependent extradiol dioxygenase, HsaC, that cleaves catechols. Immuno-compromised mice infected with a DeltahsaC mutant of M. tuberculosis H37Rv survived 50% longer than mice infected with the wild-type strain. In guinea pigs, the mutant disseminated more slowly to the spleen, persisted less successfully in the lung, and caused little pathology. These data establish that, while cholesterol metabolism by M. tuberculosis appears to be most important during the chronic stage of infection, it begins much earlier and may contribute to the pathogen's dissemination within the host. Purified HsaC efficiently cleaved the catecholic cholesterol metabolite, DHSA (3,4-dihydroxy-9,10-seconandrost-1,3,5(10)-triene-9,17-dione; k(cat)/K(m) = 14.4+/-0.5 microM(-1) s(-1)), and was inactivated by a halogenated substrate analogue (partition coefficient<50). Remarkably, cholesterol caused loss of viability in the DeltahsaC mutant, consistent with catechol toxicity. Structures of HsaC:DHSA binary complexes at 2.1 A revealed two catechol-binding modes: bidentate binding to the active site iron, as has been reported in similar enzymes, and, unexpectedly, monodentate binding. The position of the bicyclo-alkanone moiety of DHSA was very similar in the two binding modes, suggesting that this interaction is a determinant in the initial substrate-binding event. These data provide insights into the binding of catechols by extradiol dioxygenases and facilitate inhibitor design.
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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) | 0.000 | 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".