<sup>13</sup> C metabolite tracing reveals glutamine and acetate as critical in vivo fuels for CD8 <sup>+</sup> T cells
Bibliographic record
Abstract
Abstract Infusion of 13C-labeled metabolites provides a gold-standard for understanding the metabolic processes used by T cells during immune responses in vivo . Through infusion of 13C-labeled metabolites (glucose, glutamine, acetate) in Listeria monocytogenes ( Lm )-infected mice, we demonstrate that CD8+ T effector (Teff) cells utilize metabolites for specific pathways during specific phases of activation. Highly proliferative early Teff cells in vivo shunt glucose primarily towards nucleotide synthesis and leverage glutamine anaplerosis in the tricarboxylic acid (TCA) cycle to support ATP and de novo pyrimidine synthesis. Additionally, early Teff cells rely on glutamic-oxaloacetic transaminase 1 (Got1)—which regulates de novo aspartate synthesis—for effector cell expansion in vivo . Importantly, Teff cells change fuel preference over the course of infection, switching from glutamine-to acetate-dependent TCA cycle metabolism late in infection. This study provides insights into the dynamics of Teff metabolism, illuminating distinct pathways of fuel consumption associated with Teff cell function in vivo . Teaser Interrogating dynamics of fuel utilization by CD8 + T cells in vivo reveals new metabolic checkpoints for immune function in vivo .
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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) | 0.003 | 0.001 |
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".