Uptake‐independent killing of macrophages by extracellular Mycobacterium tuberculosis aggregates
Bibliographic record
Abstract
Mycobacterium tuberculosis (Mtb) infection is initiated by inhalation of bacteria into lung alveoli, where they are phagocytosed by resident macrophages. Intracellular Mtb replication induces the death of the infected macrophages and the release of bacterial aggregates. Here, we show that these aggregates can evade phagocytosis by killing macrophages in a contact-dependent but uptake-independent manner. We use time-lapse fluorescence microscopy to show that contact with extracellular Mtb aggregates triggers macrophage plasma membrane perturbation, cytosolic calcium accumulation, and pyroptotic cell death. These effects depend on the Mtb ESX-1 secretion system, however, this system alone cannot induce calcium accumulation and macrophage death in the absence of the Mtb surface-exposed lipid phthiocerol dimycocerosate. Unexpectedly, we found that blocking ESX-1-mediated secretion of the EsxA/EsxB virulence factors does not eliminate the uptake-independent killing of macrophages and that the 50-kDa isoform of the ESX-1-secreted protein EspB can mediate killing in the absence of EsxA/EsxB secretion. Treatment with an ESX-1 inhibitor reduces uptake-independent killing of macrophages by Mtb aggregates, suggesting that novel therapies targeting this anti-phagocytic mechanism could prevent the propagation of extracellular bacteria within the lung.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".