PI3K-dependant reprogramming of hexokinase isoforms controls glucose metabolism and functional responses of B lymphocytes
Bibliographic record
Abstract
Abstract B lymphocyte metabolic reprogramming is essential for B cell differentiation and mounting a healthy immune response. The PI3K signaling pathway regulates B cell metabolism, but the mechanisms involved are not well understood. Here we report that signaling via PI3K8 can impact B cell glucose metabolism and immune functions via selective upregulation of hexokinase 2 (HK2). Three HK enzymes can catalyze the critical first step for glucose utilization and may selectively direct glucose into specific catabolic and anabolic pathways. While HK1 is constitutively expressed in B cells, HK2 is strikingly upregulated during B cell activation in a PI3K8-dependent manner. HK2 shows a unique distribution between mitochondrial and cytoplasmic pools that is also regulated by PI3K. Genetic deletion of HK2 significantly impairs extracellular acidification rate and glycolytic ATP production despite strong expression of HK1. B cell-specific deletion of HK2 in mice caused mild perturbations in B cell development but did not prevent generation of mature B cell subsets. HK2-deficient B cells show altered functional responses in vitro and evidence of metabolic adaptation to become less dependent on glucose and more dependent on glutamine. HK2-deficient B cells exhibit impaired glycolysis, altered metabolite profiles and altered flux of labeled glucose carbons into the pentose phosphate pathway. Upon immunization, HK2-deficient mice exhibit impaired generation of germinal centre B cells, plasmablasts and antibody responses. We further found that HK2 expression in primary human chronic lymphocytic leukemia (CLL) cells was associated with recent proliferation and could be reduced by PI3K inhibition. Our study identifies hexokinase 2 upregulation as a functionally important component of B cell metabolic reprogramming dependent on the PI3K pathway.
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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".