TAPP Adaptors Control B Cell Metabolism by Modulating the Phosphatidylinositol 3-Kinase Signaling Pathway: A Novel Regulatory Circuit Preventing Autoimmunity
Bibliographic record
Abstract
Class I PI3K enzymes play critical roles in B cell activation by phosphorylating plasma membrane lipids to generate two distinct phosphoinositide (PI) products, PI(3,4,5)P3 and PI(3,4)P2. These PIs each bind distinct but overlapping sets of intracellular proteins that control cell survival, cytoskeletal reorganization, and metabolic activity. The tandem PH domain containing proteins (TAPPs) bind with high specificity to PI(3,4)P2, and their genetic uncoupling from PI(3,4)P2 in TAPP knock in (KI) mice was previously found to cause chronic B cell activation, abnormal germinal centers (GCs), and autoimmunity. In this article, we find that TAPPs provide feedback regulation affecting PI3K signaling and metabolic activation of B cells. Upon activation, TAPP KI B cells show enhanced metabolic activity associated with increased extracellular acidification rate, increased expression of glucose transporter GLUT1, and increased glucose uptake. TAPP KI B cells show markedly increased activation of the PI3K-regulated kinases Akt, GSK3β, and p70-S6K. Conversely, overexpression of the C-terminal TAPP PH domains in B cells can inhibit Akt phosphorylation by a mechanism requiring the TAPP PI(3,4)P2-binding pocket. Inhibition of the PI3K pathway in TAPP KI B cells reduced GLUT1 expression and glucose uptake, whereas inhibition of Akt alone was not sufficient to normalize these responses. TAPP KI GC B cells also show increased GLUT1 and glucose uptake, and treatment with the inhibitor of glycolysis 2-deoxy-D-glucose reduced chronic GC responses and autoantibody production within these mice. Our findings show that TAPP-PI(3,4)P2 interaction controls activation of glycolysis and highlights the significance of this pathway for B cell activation, GC responses, and autoimmunity.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".