Proteasome degradative activity regulates CD8+ T lymphocyte metabolism and fate specification
Bibliographic record
Abstract
Abstract During an immune response to microbial infection, CD8+ T lymphocytes can undergo asymmetric division, giving rise to daughter cells that exhibit distinct tendencies to adopt the terminal effector and memory fates. Here we show that ‘pre-effector’ and ‘pre-memory’ cells arising from the first CD8+ T cell division in vivo exhibit low and high rates of proteasome degradative activity, respectively. Pharmacologic inhibition of proteasome activity in activated CD8+ T cells resulted in increased inflammatory cytokine production and effector cell-associated molecule expression in vitro, as well as a loss of survival capacity and an impaired recall response to secondary infection in vivo. By contrast, increasing proteasome activity using a novel small molecule proteasome activator resulted in augmented memory cell-associated characteristics in vitro and an increased proportion of central memory cells with enhanced recall capabilities in vivo. Transcriptomic and proteomic analyses revealed that modulating proteasome activity in activated CD8+ T cells affected processes associated with cellular metabolism. These proteasome-induced metabolic consequences were mediated, in part, through asymmetric segregation of Myc, a transcription factor that has been shown to control glycolysis and proliferation, during cell division. Taken together, these results suggest proteasome degradative activity as a key regulator of CD8+ T lymphocyte fate specification by virtue of effects on cellular metabolism.
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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".