Deciphering the role of Klf2 in CD8 T cell differentiation and exhaustion during chronic infection
Bibliographic record
Abstract
Abstract T cell exhaustion, a state of dysfunction occurring during chronic infections and cancer, is marked by a progressive loss of effector functions and increased expression of inhibitory receptors. In chronic infection, CD8 T cells differentiate into TCF1+ progenitor (TPRO), CX3CR1+ effector (TEFF), and terminally exhausted (TEXH) subsets. The differentiation pathways are governed by complex transcription factor (TF) networks. Employing regulon analysis enabled by single-cell RNA+ATAC multiome sequencing, we dissected the TF networks orchestrating the fate of exhausted CD8 T cell populations. Our integrative analysis, complemented by single-cell CRISPR screening, highlighted Krüppel-like factor 2 (KLF2) as a pivotal TF necessary for maintaining TPRO cells and generating TEFF cells. Our research also revealed that KLF2 regulates the distinct distribution patterns of CD8 T cell subsets across organs. More intriguingly, multiomic analysis uncovered a novel function of Klf2 in limiting T cell exhaustion. Klf2-deficient CD8 T cells exhibited a marked increase in exhaustion signature genes. ATAC-seq and CUT&TAG assays further revealed different chromatin accessibility and histone modifications within Klf2 and its enhancers across CD8 T cell subsets. These insights underscore the differential transcriptional and epigenetic regulation of Klf2, presenting a novel mechanism that influences the cell fate decision of CD8 T cells during chronic infections.
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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) | 0.000 | 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 | 0.001 |
| 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".