Survival of <i>Mycobacterium tuberculosis</i> in Host Macrophages Involves Resistance to Apoptosis Dependent upon Induction of Antiapoptotic Bcl-2 Family Member Mcl-1
Bibliographic record
Abstract
Mcl-1 protein expression was found to be up-regulated during infection with virulent Mycobacterium tuberculosis strain H37Rv. Mcl-1 induction in THP-1 cells was optimal at a multiplicity of infection of 0.8-1.2 bacilli per macrophage and was independent of opsonin coating of the bacteria. Mcl-1 expression was elevated as early as 4 h, peaked at 5.8-fold above control cells at 24 h, and remained elevated at 48 h after infection. In THP-1 cells, mMcl-1 mRNA was induced by infection with live H37Rv but not with attenuated M. tuberculosis strain H37Ra, heat-killed H37Rv, or latex beads. In THP-1 cells and monocyte-derived macrophages (MDMs), Mcl-1 protein was induced by infection with live H37Rv but not with attenuated M. tuberculosis strain H37Ra, heat-killed H37Rv, or latex beads. Treatment of uninfected, H37Ra-infected, and H37Rv-infected THP-1 cells and MDMs with antisense oligonucleotides to mcl-1 reduced Mcl-1 expression by >84%. This resulted in an increase in apoptosis of both MDMs and THP-1 cells that were infected with H37Rv, but not cells that were uninfected or infected with H37Ra. Increased apoptosis correlated with a decrease in M. tuberculosis CFUs recovered from antisense-treated, H37Rv-infected cells at 4 and 7 days after infection. In contrast, CFU recoveries from sense-treated, H37Rv-infected cells or from antisense- or sense-treated, H37Ra-infected cells were unchanged from controls. Thus, the antiapoptotic effect of the induction of Mcl-1 expression in H37Rv-infected macrophages promotes the survival of virulent M. tuberculosis.
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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".