MRP1 inhibition by lipid-derived electrophiles during ferroptosis illustrates a role for protein alkylation in ferroptotic cell death
Bibliographic record
Abstract
Abstract Ferroptosis is a regulated form of cell death characterized by lipid peroxidation and lipid hydroperoxide (LOOH) generation that offers new therapeutic opportunities. However, the molecular mechanism through which LOOH accumulation leads to cell death remains poorly understood. Importantly, LOOH breakdown forms truncated phospholipids (PLs) and highly reactive lipid-derived electrophiles (LDEs) capable of altering protein function through cysteine alkylation. While truncated PLs have been shown to mediate ferroptotic membrane permeabilization, a functional role for LDEs in the ferroptotic cell death mechanism has not been established. Here, using multidrug resistance protein 1 (MRP1) activity as an example, we demonstrate that LDEs mediate altered protein function during ferroptosis . Applying live cell fluorescence imaging, we first identified that inhibition of MRP1-mediated LDE detoxification occurs across a panel of ferroptosis inducers (FINs) with differing mechanisms of ferroptosis induction (Types I-IV FINs erastin, RSL3, FIN56 and FINO 2 ). This MRP1 inhibition was recreated by both initiation of lipid peroxidation and treatment with the LDE 4-hydroxy-2-nonenal (4-HNE). Importantly, treatment with radical-trapping antioxidants prevented impaired MRP1 activity when working with both FINs and lipid peroxidation initiators but not 4-HNE, pinpointing LDEs as the cause of inhibited MRP1 activity during ferroptosis. Our findings, when combined with reports of widespread LDE-alkylation of key proteins during ferroptosis, sets a precedent for LDEs as critical mediators of ferroptotic cell death. LOOH breakdown to truncated phospholipids and LDEs may fully explain membrane permeabilization and modified protein function during late stage ferroptosis, offering a unified explanation of the molecular ferroptotic cell death mechanism.
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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".