Vacuolar-ATPase inhibitors are antimicrobial agents active against intracellular mycobacteria
Bibliographic record
Abstract
ABSTRACT Mycobacterium tuberculosis (Mtb) evades host defenses by inhibiting phagosome acidification in part through the secreted phosphatase PtpA, binding to the vacuolar ATPase (v-ATPase), and disrupting downstream cellular events. We investigated the antimicrobial effects of three v-ATPase inhibitors, Bafilomycin A1 (BafA1), Bafilomycin D, and Cladoniamide B (ClaB), on the growth of Mtb, M. abscessus (Mabs), and M. bovis BCG in THP-1 and murine infection models. We found potent inhibition of intracellular growth with MIC 50 in the nanomolar range, with compounds showing a bacteriostatic inhibition of Mtb growth in THP-1 macrophages. Axenic bacteria were not affected by 2 µM compound in broth, although lysate from macrophages incubated with ClaB resulted in a 50% reduction in bacterial growth in broth, which was further enhanced by the addition of zinc. We further discovered that BafA1 amplifies the cytotoxic effects of Mtb infection and limits Mtb’s ability to delay apoptosis in host cells. BafA1 antimicrobial activity was abolished in Mtb PtpA knockout mutant, and BafA1 binding to PtpA was shown via an in vitro thermal shift assay. Our findings reveal a complex interplay between v-ATPase inhibition, host cell responses, and bacterial survival, challenging traditional views on phagosome acidification in pathogenesis and suggesting novel avenues for host-directed therapies against intracellular mycobacterial infections.
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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 | 0.000 |
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".