Abstract IA22: Regulation of metabolic plasticity in effector T cells
Bibliographic record
Abstract
Abstract T lymphocytes are central effectors of the adaptive immune response, and their proper function is critical for long-lasting immunity to foreign pathogens and tumor immunosurveillance. One of the fundamental programs triggered by T cell activation is the reprogramming of cellular metabolism, which is essential to support the bioenergetic and biosynthetic demands of effector T (Teff) cell function. While often considered a “housekeeping” function, cellular metabolism has recently been linked to proper Teff cell differentiation and effector function in vivo, raising the idea that nutrient availability can be immunomodulatory. However, how nutrient availability shapes T cell metabolism and function remains poorly understood. Here we present evidence suggesting that effector T cells possess “metabolic plasticity” and are capable of altering their metabolic programs in response to nutrient availability. We show that T cells possess a glucose-sensitive metabolic checkpoint controlled by the energy sensor AMP-activated protein kinase (AMPK) that regulates cellular bioenergetics and T cell viability. Effector T cells lacking AMPKα1 display reduced mitochondrial bioenergetics and cellular ATP in response to glucose limitation in vitro or pathogenic challenge in vivo. Finally, we find that AMPKα1 is essential for robust CD4+ and CD8+ T cell responses to viral and bacterial infections in vivo. Our data highlight AMPK-dependent regulation of metabolic homeostasis as a key regulator of T cell-mediated adaptive immunity. These results and the use AMPK agonists to regulate T cell function will be discussed. Citation Format: Russell Graham Jones. Regulation of metabolic plasticity in effector T cells. [abstract]. In: Proceedings of the AACR Special Conference: Tumor Immunology and Immunotherapy: A New Chapter; December 1-4, 2014; Orlando, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2015;3(10 Suppl):Abstract nr IA22.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".