An intrinsic lipid-binding interface controls sphingosine kinase 1 function
Bibliographic record
Abstract
Sphingosine kinase 1 (SK1) is required for production of sphingosine-1-phosphate (S1P) and thereby regulates many cellular processes, including cellular growth, immune cell trafficking, and inflammation. To produce S1P, SK1 must access sphingosine directly from membranes. However, the molecular mechanisms underlying SK1's direct membrane interactions remain unclear. We used hydrogen/deuterium exchange MS to study interactions of SK1 with membrane vesicles. Using the CRISPR/Cas9 technique to generate HCT116 cells lacking SK1, we explored the effects of membrane interface disruption and the function of the SK1 interaction site. Disrupting the interface resulted in reduced membrane association and decreased cellular SK1 activity. Moreover, SK1-dependent signaling, including cell invasion and endocytosis, was abolished upon mutation of the membrane-binding interface. Of note, we identified a positively charged motif on SK1 that is responsible for electrostatic interactions with membranes. Furthermore, we demonstrated that SK1 uses a single contiguous interface, consisting of an electrostatic site and a hydrophobic site, to interact with membrane-associated anionic phospholipids. Altogether, these results define a composite domain in SK1 that regulates its intrinsic ability to bind membranes and indicate that this binding is critical for proper SK1 function. This work will allow for a new line of thinking for targeting SK1 in disease.
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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 | 0.001 |
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".