Metabolic adaptation of glucose-deprived macrophages involves partial gluconeogenesis
Bibliographic record
Abstract
Macrophages are recruited to sites of infection contributing to the killing of bacteria, but also to malignant tumors, where they promote angiogenesis and suppress antitumor immune responses. The metabolic microenvironment in tumors is frequently depleted of important nutrients such as glucose. Here, we investigated metabolic adaptation strategies of macrophages to glucose deprivation using stable isotopic tracing. Lactate production was decreased, potentially indicating a reduction of glycolysis. In contrast, the contribution of glutamine to the tricarboxylic acid cycle via α-ketoglutarate and reductive carboxylation were increased. Moreover, gluconeogenesis, the reverse pathway of glycolysis, was activated in glucose-deprived macrophages, proceeding partially to the generation of glycolytic intermediates and glycerol-3-phosphate. The partial gluconeogenesis pathway was abrogated in human and murine macrophages lacking the initial gluconeogenic enzyme phosphoenolpyruvate carboxykinase (PCK2, mitochondrial isoform). Partial gluconeogenesis was higher in anti-inflammatory, interleukin-4-stimulated compared to proinflammatory, interferon-γ/lipopolysaccharide-stimulated macrophages. Single-cell analysis and immunostaining revealed expression of PCK2 in macrophages from both lung cancer and normal lung. Low glucose conditions only partially modulated macrophage phenotypes, leading to reduced CD80 surface marker levels in proinflammatory, and enhanced vascular endothelial growth factor expression in anti-inflammatory macrophages. Our study reveals partial gluconeogenesis in glucose-deprived macrophages and shows that this versatile type of immune cells exhibits remarkable metabolic flexibility.
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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) | 0.000 | 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 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".