Beta Interferon Regulation of Glucose Metabolism Is PI3K/Akt Dependent and Important for Antiviral Activity against Coxsackievirus B3
Bibliographic record
Abstract
UNLABELLED: An effective type I interferon (IFN)-mediated immune response requires the rapid expression of antiviral proteins that are necessary to inhibit viral replication and virus spread. We provide evidence that IFN-β regulates metabolic events important for the induction of a rapid antiviral response: IFN-β decreases the phosphorylation of AMP-activated protein kinase (AMPK), coincident with an increase in intracellular ATP. Our studies reveal a biphasic IFN-β-inducible uptake of glucose by cells, mediated by phosphatidylinositol 3-kinase (PI3K)/Akt, and IFN-β-inducible regulation of GLUT4 translocation to the cell surface. Additionally, we provide evidence that IFN-β-regulated glycolytic metabolism is important for the acute induction of an antiviral response during infection with coxsackievirus B3 (CVB3). Last, we demonstrate that the antidiabetic drug metformin enhances the antiviral potency of IFN-β against CVB3 both in vitro and in vivo. Taken together, these findings highlight an important role for IFN-β in modulating glucose metabolism during a virus infection and suggest that the use of metformin in combination with IFN-β during acute virus infection may result in enhanced antiviral responses. IMPORTANCE: Type I interferons (IFN) are critical effectors of an antiviral response. These studies describe for the first time a role for IFN-β in regulating metabolism--glucose uptake and ATP production--to meet the energy requirements of a robust cellular antiviral response. Our data suggest that IFN-β regulates glucose metabolism mediated by signaling effectors similarly to activation by insulin. Interference with IFN-β-inducible glucose metabolism diminishes the antiviral response, whereas treatment with metformin, a drug that increases insulin sensitivity, enhances the antiviral potency of IFN-β.
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) | 0.001 | 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 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".