CD8 <sup>+</sup> T-Cell Metabolic Rewiring Defined by Single-Cell RNA-Sequencing Identifies a Critical Role of ASNS Expression Dynamics in T-Cell Differentiation
Bibliographic record
Abstract
ABSTRACT Cytotoxic T cells dynamically rewire their metabolism during the course of an immune response. While T-cell metabolism has been extensively studied at phenotypic endpoints of activation and differentiation, the underlying dynamics remain largely elusive. Here, we leverage on single-cell RNA-sequencing (scRNA-seq) measurements of in vitro activated and differentiated CD8 + T cells cultured in physiological media to resolve these metabolic dynamics. We find that our scRNA-seq analysis identifies most metabolic changes previously defined in in vivo experiments, such as a rewiring from an oxidative to an anabolism-promoting metabolic program during activation to an effector state, which is later reverted upon memory polarization. Importantly, our scRNA-seq data further provide a dynamic description of these changes. In this sense, our data predict a differential time-dependent reliance of CD8 + T cells on the synthesis versus uptake of various non-essential amino acids during T-cell activation, which we corroborate with additional functional in vitro experiments. We further exploit our scRNA-seq data to identify metabolic genes that could potentially dictate the outcome of T-cell differentiation, by ranking them based on their expression dynamics. Among the highest-ranked hits, we find asparagine synthetase ( Asns ), whose expression sharply peaks for effector CD8 + T cells and further decays towards memory polarization. We then confirm that these in vitro Asns expression dynamics are representative of an in vivo situation in a mouse model of viral infection. Moreover, we find that disrupting these expression dynamics in vitro , by depleting asparagine from the culture media, delays central-memory polarization. Accordingly, we find that preventing the decay of ASNS by stable overexpression at the protein level in vivo leads to a significant increase in effector CD8 + T-cell expansion, and a concomitant decrease in central-memory formation, in a mouse model of viral infection. This shows that ASNS expression dynamics dictate the fate of CD8 + T-cell differentiation. In conclusion, we provide a resource of dynamic expression changes during CD8 + T-cell activation and differentiation that is expected to increase our understanding of the dynamic metabolic requirements of T cells progressing along the immune response cascade.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".