IL-15Rα-Independent IL-15 Signaling in Non-NK Cell-Derived IFNγ Driven Control of Listeria monocytogenes
Bibliographic record
Abstract
Interleukin-15, produced by hematopoietic and parenchymal cells, maintains immune cell homeostasis and facilitates activation of lymphoid and myeloid cell subsets. IL-15 interacts with the ligand-binding receptor chain IL-15Rα during biosynthesis, and the IL-15:IL-15Rα complex is trans-presented to responder cells that express the IL-2/15Rβγ c complex to initiate signaling. IL-15-deficient and IL-15Rα-deficient mice display similar alterations in immune cell subsets. Thus, the trimeric IL-15Rαβγ c complex is considered the functional IL-15 receptor. However, studies on the pathogenic role of IL-15 in inflammatory and autoimmune diseases indicate that IL-15 can signal independently of IL-15Rα via the IL-15Rβγ c dimer. Here, we compared the ability of mice lacking IL-15 (no signaling) or IL-15Rα (partial/distinct signaling) to control Listeria monocytogenes infection. We show that IL-15-deficient mice succumb to infection whereas IL-15Rα-deficient mice clear the pathogen as efficiently as wildtype mice. IL-15-deficient macrophages did not show any defect in bacterial uptake or iNOS expression in vitro . In vivo , IL-15 deficiency impaired the accumulation of inflammatory monocytes in infected spleens without affecting chemokine and pro-inflammatory cytokine production. The inability of IL-15-deficient mice to clear L. monocytogenes results from impaired early IFNγ production, which was not affected in IL-15Rα-deficient mice. Administration of IFNγ partially enabled IL-15-deficient mice to control the infection. Bone marrow chimeras revealed that IL-15 needed for early bacterial control can originate from both hematopoietic and non-hematopoietic cells. Overall, our findings indicate that IL-15-dependent IL-15Rα-independent signaling via the IL-15Rβγ c dimeric complex is necessary and sufficient for the induction of IFNγ from sources other than NK/NKT cells to control bacterial pathogens.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".