Diversity in Cortical Thymic Epithelial Cells Occurs through Loss of a Foxn1-Dependent Gene Signature Driven by Stage-Specific Thymocyte Cross-Talk
Bibliographic record
Abstract
In the thymus, cortical thymic epithelial cells (cTECs) and medullary thymic epithelial cells support αβT cell development from lymphoid progenitors. For cTECs, expression of a specialized gene signature that includes Cxcl12, Dll4, and Psmb11 enables the cortex to support T lineage commitment and the generation and selection of CD4+CD8+ thymocytes. Although the importance of cTECs in T cell development is well defined, mechanisms that shape the cTEC compartment and regulate its functional specialization are unclear. Using a Cxcl12DsRed reporter mouse model, we show that changes in Cxcl12 expression reveal a developmentally regulated program of cTEC heterogeneity. Although cTECs are uniformly Cxcl12DsRed+ during neonatal stages, progression through postnatal life triggers the appearance of Cxcl12DsRed- cTECs that continue to reside in the cortex alongside their Cxcl12DsRed+ counterparts. This appearance of Cxcl12DsRed- cTECs is controlled by maturation of CD4-CD8-, but not CD4+CD8+, thymocytes, demonstrating that stage-specific thymocyte cross-talk controls cTEC heterogeneity. Importantly, although fate-mapping experiments show both Cxcl12DsRed+ and Cxcl12DsRed- cTECs share a common Foxn1+ cell origin, RNA sequencing analysis shows Cxcl12DsRed- cTECs no longer express Foxn1, which results in loss of the FOXN1-dependent cTEC gene signature and may explain the reduced capacity of Cxcl12DsRed- cTECs for thymocyte interactions. In summary, our study shows that shaping of the cTEC compartment during the life course occurs via stage-specific thymocyte cross-talk, which drives loss of Foxn1 expression and its key target genes, which may then determine the functional competence of the thymic cortex.
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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 | 0.001 |
| 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".