The Transcription Factors TFEB and TFE3 Link the FLCN-AMPK Signaling Axis to Innate Immune Response and Pathogen Resistance
Bibliographic record
Abstract
TFEB and TFE3 are transcriptional regulators of the innate immune response, but the mechanisms regulating their activation upon pathogen infection are poorly elucidated. Using C. elegans and mammalian models, we report that the master metabolic modulator 5'-AMP-activated protein kinase (AMPK) and its negative regulator Folliculin (FLCN) act upstream of TFEB/TFE3 in the innate immune response, independently of the mTORC1 signaling pathway. In nematodes, loss of FLCN or overexpression of AMPK confers pathogen resistance via activation of TFEB/TFE3-dependent antimicrobial genes, whereas ablation of total AMPK activity abolishes this phenotype. Similarly, in mammalian cells, loss of FLCN or pharmacological activation of AMPK induces TFEB/TFE3-dependent pro-inflammatory cytokine expression. Importantly, a rapid reduction in cellular ATP levels in murine macrophages is observed upon lipopolysaccharide (LPS) treatment accompanied by an acute AMPK activation and TFEB nuclear localization. These results uncover an ancient, highly conserved, and pharmacologically actionable mechanism coupling energy status with innate immunity.
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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".