Engagement of the Aryl Hydrocarbon Receptor in <i>Mycobacterium tuberculosis</i>–Infected Macrophages Has Pleiotropic Effects on Innate Immune Signaling
Bibliographic record
Abstract
Understanding the mechanisms of host macrophage responses to Mycobacterium tuberculosis is essential for uncovering potential avenues of intervention to boost host resistance to infection. Macrophage transcriptome profiling revealed that M. tuberculosis infection strongly induced the expression of several enzymes controlling tryptophan catabolism. These included IDO1 and tryptophan 2,3-dioxygenase, which catalyze the rate-limiting step in the kynurenine pathway, producing ligands for the aryl hydrocarbon receptor (AHR). The AHR and heterodimeric partners AHR nuclear translocator and RELB are robustly expressed, and AHR and RELB levels increased further during infection. Infection enhanced AHR/AHR nuclear translocator and AHR/RELB DNA binding and stimulated the expression of AHR target genes, including that encoding the inflammatory cytokine IL-1β. AHR target gene expression was further enhanced by exogenous kynurenine, and exogenous tryptophan, kynurenine, or synthetic agonist indirubin reduced mycobacterial viability. Comparative expression profiling revealed that AHR ablation diminished the expression of numerous genes implicated in innate immune responses, including several cytokines. Notably, AHR depletion reduced the expression of IL23A and IL12B transcripts, which encode subunits of IL-23, a macrophage cytokine that stimulates production of IL-22 by innate lymphoid cells. AHR directly induced IL23A transcription in human and mouse macrophages through near-upstream enhancer regions. Taken together, these findings show that AHR signaling is strongly engaged in M. tuberculosis-infected macrophages and has widespread effects on innate immune responses. Moreover, they reveal a cascade of AHR-driven innate immune signaling, because IL-1β and IL-23 stimulate T cell subsets producing IL-22, another direct target of AHR transactivation.
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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 | 0.001 |
| 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".