Abelson Tyrosine Kinase Controls Phagosomal Acidification Required for Killing of <i>Mycobacterium tuberculosis</i> in Human Macrophages
Bibliographic record
Abstract
The mechanisms that regulate the acidification of intracellular compartments are key to host defense against pathogens. In this paper, we demonstrate that Abl tyrosine kinase, a master switch for cell growth and trafficking of intracellular organelles, controls the acidification of lysosomes in human macrophages. Pharmacological inhibition by imatinib and gene silencing of Abelson (Abl) tyrosine kinase reduced the lysosomal pH in human macrophages by increasing the transcription and expression of the proton pumping enzyme vacuolar-type H(+)-adenosine triphosphatase. Because lysosomal acidification is required for antimicrobial activity against intracellular bacteria, we determined the effect of imatinib on the growth of the major human pathogen Mycobacterium tuberculosis. Imatinib limited the multiplication of M. tuberculosis, and growth restriction was dependent on acidification of the mycobacterial compartment. The effects of imatinib were also active in vivo because circulating monocytes from imatinib-treated leukemia patients were more acidic than monocytes from control donors. Importantly, sera from imatinib-treated patients triggered acidification and growth restriction of M. tuberculosis in macrophages. In summary, our results identify the control of phagosomal acidification as a novel function of Abl tyrosine kinase and provide evidence that the regulation occurs on the level of the vacuolar-type H(+)-adenosine triphosphatase. Given the efficacy of imatinib in a mouse model of tuberculosis and our finding that orally administered imatinib increased the ability of human serum to trigger growth reduction of intracellular M. tuberculosis, clinical evaluation of imatinib as a complementary therapy of tuberculosis, in particular multidrug or extremely drug-resistant disease, is warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".