Cross-species analyses reveal RORγt-expressing dendritic cells are a lineage of antigen presenting cells conserved across tissues
Bibliographic record
Abstract
Abstract Conventional dendritic cells (cDCs) are potent antigen presenting cells (APCs) that exhibit tissue and age-specific diversity allowing them to direct situation-adapted immunity. Thereby they harbor great potential for being targeted in vaccination and cancer. Here, we resolve conflicting data about expression of retinoic acid receptor-related orphan receptor-γt (RORψt) in cDCs. We show that RORψt + DCs exist in murine lymphoid and non-lymphoid tissues across age. Fate mapping, functional assays and single cell multiomic profiling reveal these cells as ontogenetically and transcriptionally distinct from other well characterized cDC subtypes, as well as from RORψt + type 3 innate lymphocytes (ILC3s). We show that RORψt + DCs can migrate to lymph nodes and activate naïve CD4 + T cells in response to inflammatory triggers. Comparative and cross-species transcriptomics revealed homologous populations in human spleen, lymph nodes and intestines. Further, integrated meta-analyses aligned RORψt + DCs identified here with other emerging populations of RORψt + APCs, including R-DC-like cells, Janus cells/extrathymic Aire expressing cells (eTACs) and subtypes of Thetis cells. While RORψt + APCs have primarily been linked to T cell tolerance, our work establishes RORψt + DCs as unique lineage of immune sentinel cells conserved across tissues and species that expands the functional repertoire of RORψt + APCs beyond promoting tolerance. One sentence summary RORγt + DC exhibit versatile APC functions and are a distinct immune lineage conserved across age, tissues and species that entails Thetis cells, Janus cells/RORγt + eTACs and R-DC-like cells.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".