FLT4/VEGFR3 activates AMPK to coordinate glycometabolic reprogramming with autophagy and inflammasome activation for bacterial elimination
Bibliographic record
Abstract
Macrophages rapidly undergo glycolytic reprogramming in response to macroautophagy/autophagy, inflammasome activation and pyroptosis for the clearance of bacteria. Identification the key molecules involved in these three events will provide critical potential therapeutic applications. Upon S. typhimurium infection, FLT4/VEGFR3 and its ligand VEGFC were inducibly expressed in macrophages, and FLT4 signaling inhibited CASP1 (caspase 1)-dependent inflammasome activation and pyroptosis but enhanced MAP1LC3/LC3 activation for elimination of the bacteria. Consistently, FLT4 mutants lacking the extracellular ligand-binding domain increased production of the proinflammatory metabolites such as succinate and lactate, and reduced antimicrobial metabolites including citrate and NAD(P)H in macrophages and liver upon infection. Mechanistically, FLT4 recruited AMP-activated protein kinase (AMPK) and phosphorylated Y247 and Y441/442 in the PRKAA/alpha subunit for AMPK activation. The AMPK agonist AICAR could rescue glycolytic reprogramming and inflammasome activation in macrophages expressing the mutant FLT4, which has potential translational application in patients carrying Flt4 mutations to prevent recurrent infections. Collectively, we have elucidated that the FLT4-AMPK module in macrophages coordinates glycolytic reprogramming, autophagy, inflammasome activation and pyroptosis to eliminate invading bacteria.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.087 | 0.035 |
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".