Deciphering the biosynthesis of a novel lipid in Mycobacterium tuberculosis expands the known roles of the nitroreductase superfamily
Bibliographic record
Abstract
Mycobacterium tuberculosis 's (Mtb) success as a pathogen is due in part to its sophisticated lipid metabolic programs, both catabolic and biosynthetic. Several of Mtb's lipids have specific roles in pathogenesis, but the identity and roles of many are unknown. Here, we demonstrated that the tyz gene cluster in Mtb, previously implicated in resistance to oxidative stress and survival in macrophages, encodes the biosynthesis of acyl-oxazolones. Heterologous expression of tyzA ( Rv2336 ), tyzB ( Rv2338c ) and tyzC ( Rv2337c ) resulted in the biosynthesis of C 12:0 -tyrazolone as the predominant compound, and the C 12:0 -tyrazolone was identified in Mtb lipid extracts. TyzA catalyzed the N -acylation of L-amino acids, with highest specificity for L-Tyr and L-Phe and lauroyl-CoA ( k cat / K M = 5.9 ± 0.8 × 10 3 M -1 s -1 ). In cell extracts, TyzC, a flavin-dependent oxidase (FDO) of the nitroreductase (NTR) superfamily, catalyzed the O 2 -dependent desaturation of the N- acyl-L-Tyr produced by TyzA, while TyzB, a ThiF homolog, catalyzed its ATP-dependent cyclization. The substrate preference of TyzB and TyzC appear to determine the identity of the acyl-oxazolone. Phylogenetic analyses revealed that the NTR superfamily includes a large number of broadly distributed FDOs, including five in Mtb that likely catalyze the desaturation of lipid species. Finally, TCA1, a molecule with activity against drug-resistant and persistent tuberculosis, failed to inhibit the cyclization activity of TyzB, the proposed secondary target of TCA1. Overall, this study identifies a novel class of Mtb lipids, clarifies the role of a potential drug target, and expands our understanding of the NTR superfamily.
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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".