Myristic Acid Remodels Sphingolipid Metabolism via Dual Pathways: Canonical d18-Sphingolipid Regulation and Non-Canonical d16-Sphingolipid Synthesis
Bibliographic record
Abstract
Background: Myristic acid (MA), a 14-carbon saturated fatty acid, serves as a precursor for the synthesis of non-canonical d16-sphingoid bases via its activated form, C14:0-CoA. However, its broader regulatory role in sphingolipid (SL) metabolism remains poorly defined. Methods: Using HepG2 cells treated with 50 μM MA, we found that sphingolipidomic analysis revealed reprogrammed sphingolipid metabolism. Results: In the canonical d18-SL pathway, MA directs its activated product C14:0-CoA into ceramide N-acyl chains and downstream metabolites—especially d18:1-C14:0 hexosylceramide. Concurrently, in the non-canonical d16-SL pathway, MA promotes d16-SL synthesis, especially d16:1-ceramides (Cer), d16:1-hexosylceramides (HexCer), and d16:1-C14:0 lactosylceramide. MA treatment further induced a coordinated shift in cellular sphingolipid pools, characterized by a significant increase in total ceramide levels (encompassing both d16- and d18-species) alongside concurrent reductions in total sphingomyelin (SM) contents. At the gene transcriptional level, MA significantly suppressed SPTLC2 mRNA expression while markedly upregulating SMPD2 and SMPD3 mRNA levels. Conclusions: Collectively, these findings position MA as a potent regulator of sphingolipid homeostasis, orchestrating dual pathway modulation: disrupting canonical d18-SL equilibrium through the selective enrichment of N-acyl C14:0-containing SLs, and activating non-canonical d16-SL synthesis. This dual pathway regulation reveals that dietary saturated fatty acids exploit sphingolipid subnetworks to regulate lipid metabolism. The interplay between dietary fatty acids and sphingolipid metabolism still requires deeper exploration. Our findings offer preliminary insights into their roles in regulating both normal and disease-associated lipid metabolism, setting the stage for subsequent mechanistic investigations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".