SLIT2/ROBO1 signaling suppresses mTORC1 for organelle control and bacterial killing
Bibliographic record
Abstract
SLIT/ROBO signaling impacts many aspects of tissue development and homeostasis, in part, through the regulation of cell growth and proliferation. Recent studies have also linked SLIT/ROBO signaling to the regulation of diverse phagocyte functions. However, the mechanisms by which SLIT/ROBO signaling acts at the nexus of cellular growth control and innate immunity remain enigmatic. Here, we show that SLIT2-mediated activation of ROBO1 leads to inhibition of mTORC1 kinase activity in macrophages, leading to dephosphorylation of its downstream targets, including transcription factor EB and ULK1. Consequently, SLIT2 augments lysosome biogenesis, potently induces autophagy, and robustly promotes the killing of bacteria within phagosomes. Concordant with these results, we demonstrate decreased lysosomal content and accumulated peroxisomes in the spinal cords of embryos from Robo1 −/− , Robo2 −/− double knockout mice. We also show that impediment of auto/paracrine SLIT-ROBO signaling axis in cancer cells leads to hyperactivation of mTORC1 and inhibition of autophagy. Together, these findings elucidate a central role of chemorepellent SLIT2 in the regulation of mTORC1 activity with important implications for innate immunity and cancer cell survival.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".