GITR induced transcriptional co-regulator PRDM16 selectively enhances T cell memory in the lung tissue following respiratory influenza infection 4025
Bibliographic record
Abstract
Abstract Description GITR, a costimulatory TNFR superfamily member plays an important role in effector and memory CD8 T cell accumulation in the lung following influenza A virus infection (IAV). PRDM16 is a transcriptional coregulator known for its role in fatty acid metabolism and mitochondrial biogenesis in brown adipose tissue and hematopoietic stem cells. We previously identified Prdm16 as one of the most significantly upregulated genes induced by GITR signaling during chronic LCMV infection (Chang et al. Immunity 2017). Here we show that conditional knockout of Prdm16 in T cells results in a selective defect in effector and tissue resident memory CD8 T cells in the lung tissue with minimal effects in the secondary lymphoid organs and a trend towards increased Teffector responses in the lung during respiratory IAV infection. Conversely, overexpression of Prdm16 in OT-I T cells followed by adoptive transfer and IAV infection resulted in decreased effector T cell responses but increased memory T cell responses in the lung tissue compared to mock transduced OT-I T cells. Single cell RNA-sequencing of WT and Prdm16-/- CD8 T cells from mixed bone marrow chimeras following IAV infection suggests that PRDM16 induces a distinct state in the WT effector T cells that is not observed in the Prdm16-/- T cells. Our study identifies PRDM16 as an important regulator of memory T cells in the lung tissue with work in progress to identify mechanism. Funding Sources Funding: This research was supported by Canadian Institutes for health research grants #FDN-143250 and PJT-178020 (to T.H.W),an Ontario Graduate Scholarship (to KY) and Emerging & Pandemic Infections Consortium Doctoral Awards to S.L. and K.Y. T.H.W. holds the Canada research chair in anti-viral immunity at the University of Toronto. Topic Categories Viral Immunology (VIR)
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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) | 0.002 | 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".