LAPTM5 Protein Is a Positive Regulator of Proinflammatory Signaling Pathways in Macrophages
Bibliographic record
Abstract
LAPTM5 (lysosomal-associated protein transmembrane 5) is a protein that is preferentially expressed in immune cells, and it interacts with the Nedd4 family of ubiquitin ligases. Recent studies in T and B cells identified LAPTM5 as a negative regulator of T and B cell receptor levels at the plasma membrane. Here we investigated the function of LAPTM5 in macrophages. We demonstrate that expression of LAPTM5 is required for the secretion of proinflammatory cytokines in response to Toll-like receptor ligands. We also show that RAW264.7 cells knocked down for LAPTM5 or macrophages from LAPTM5(-/-) mice exhibit reduced activation of NF-κB and MAPK signaling pathways mediated by the TNF receptor, as well as multiple pattern recognition receptors in various cellular compartments. TNF stimulation of LAPTM5-deficient macrophages leads to reduced ubiquitination of RIP1 (receptor-interacting protein 1), suggesting a role for LAPTM5 at the receptor-proximate level. Interestingly, we find that macrophages from LAPTM5(-/-) mice display up-regulated levels of A20, a ubiquitin-editing enzyme responsible for deubiquitination of RIP1 and subsequent termination of NF-κB activation. Our studies thus indicate that, in contrast to its negative role in T and B cell activation, LAPTM5 acts as a positive modulator of inflammatory signaling pathways and hence cytokine secretion in macrophages. They also highlight a role for the endosomal/lysosomal system in regulating signaling via cytokine and pattern recognition receptors.
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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 | 0.000 |
| 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".