The NLRP3 inflammasome modulates glycolysis by increasing PFKFB3 in an IL-1β-dependent manner in macrophages
Bibliographic record
Abstract
Infammation and metabolism are intricately linked during infammatory diseases in which\nactivation of the nucleotide-binding domain–like receptors Family Pyrin Domain Containing 3\n(NLRP3) infammasome, an innate immune sensor, is critical. Several factors can activate the NLRP3\ninfammasome, but the nature of the link between NLRP3 infammasome activation and metabolism\nremains to be thoroughly explored. This study investigates whether the small molecule inhibitor of\nthe NLRP3 infammasome, MCC950, modulates the lipopolysaccharide (LPS) -and amyloid-β (Aβ)-\ninduced metabolic phenotype and infammatory signature in macrophages. LPS+Aβ induced IL-1β\nsecretion, while pre-treatment with MCC950 inhibited this. LPS+Aβ also upregulated IL-1β mRNA\nand supernatant concentrations of TNFα, IL-6 and IL-10, however these changes were insensitive to\nMCC950, confrming that MCC950 specifcally targets infammasome activation in BMDMs. LPS+Aβ\nincreased glycolysis and the glycolytic enzyme, PFKFB3, and these efects were decreased by MCC950.\nThese fndings suggest that NLRP3 infammasome activation may play a role in modulating glycolysis.\nTo investigate this further, the efect of IL-1β on glycolysis was assessed. IL-1β stimulated glycolysis\nand PFKFB3, mimicking the efect of LPS+Aβ and adding to the evidence that infammasome\nactivation impacts on metabolism. This contention was supported by the fnding that the LPS+Aβinduced changes in glycolysis and PFKFB3 were attenuated in BMDMs from NLRP3-defcient and\nIL-1R1-defcient mice. Consistent with a key role for PFKFB3 is the fnding that the PFKFB3 inhibitor,\n3PO, attenuated the LPS+Aβ-induced glycolysis. The data demonstrate that activation of the NLRP3\ninfammasome, and the subsequent release of IL-1β, play a key role in modulating glycolysis via\nPFKFB3. Reinstating metabolic homeostasis by targeting the NLRP3 infammasome-PFKFB3 axis may\nprovide a novel therapeutic target for treatment of acute and chronic disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".