The response of CD8 T cells to antigenic stimulation is controlled by their endogenous circadian clock
Bibliographic record
Abstract
Abstract Circadian clocks control various aspects of the immune system in mammals but their role in the adaptive immune response remains poorly defined. Our previous work showed that the CD8 T cell response to vaccination with dendritic cells loaded with the OVA peptide (DC-OVA) varies according to the time of day. In this study, we have identified the clock involved in the in vivo CD8 T cell response and have started to uncover how the circadian clock affects this response. Using Kb-OVA tetramer staining, we found that the higher expansion of OVA-specific CD8 T cells in response to DC-OVA vaccination done in the middle of the day is abolished when CD8 T cells are deficient for the essential clock gene Bmal1. Similarly, the rhythm of cytokine production by CD8 T cells was abolished. Moreover, the observed rhythm impacts the ability to control an infectious challenge (by Listeria monocytogenes) as shown by a day/night variation in bacterial load in WT but not CD8 T cell-specific Bmal1 KO mice. In contrast, the rhythm of CD8 T cell response was not affected when Bmal1 KO DCs were used to vaccinate mice, confirming the role of the CD8 T cell clock in this rhythm. To assess whether the circadian clock affected the magnitude of the CD8 T cell response by modulating the affinity of the T cells recruited in the response, we measured CD8 T cell sensitivity to restimulation with various doses of OVA peptide. A stronger T cell expansion in response to antigen presentation correlated with an increased EC50, suggesting that the CD8 T cell clock acts by recruiting CD8 T cell clones bearing TCR with different affinities for the antigen. In conclusion, the CD8 T cell clock is essential for the rhythm of the CD8 T cell response and affects the affinity of the antigen-specific CD8 T cell response.
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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".