Abstract 2440 Regulation of the Mitochondrial Pyruvate Carrier by the Wnt/beta-catenin pathway
Bibliographic record
Abstract
Metabolism is one of the most tightly regulated cellular processes important for the maintenance of homeostasis. The mitochondrial pyruvate carrier (MPC) is a transmembrane protein that resides in the inner mitochondria membrane and facilitates the entry of pyruvate, which is necessary in several metabolic reactions such as TCA cycle. Our lab has previously shown that MPC expression is negatively correlated with Wnt/β-catenin target genes; however, the molecular mechanism behind the regulation of the MPC by the Wnt/β-catenin signaling pathway is not known. Based on our preliminary observations, we hypothesize that β-catenin acts as a repressor of the MPC. To investigate this regulation, we first performed a Fluorescence-activated cell sorting (FACS)-based genetic screening assay in liver cancer cells and found that β-catenin acts as a genetic repressor of the MPC. Furthermore, we treated liver cancer cells for 48h with GSK3 inhibitors (CHIR99021 or LY2090314) to activate the Wnt/β-catenin pathway, and MPC protein was analyzed by western blot. Interestingly, we found that MPC protein was reduced in cells treated with CHIR99021 or LY2090314 when compared to untreated cells. To investigate whether MPC expression was affected at the transcriptional level, we performed RT-qPCR and found that MPC1 and MPC2 transcripts were decreased in liver cancer cells treated with CHIR99021 or LY2090314. Overall, our results suggest that activation of β-catenin results in decreased MPC transcripts and protein levels. Taken together, we proposed a model where β-catenin acts as a repressor of the MPC in liver cancer cells. Future studies will be focus on characterizing the mechanism by which MPC expression is regulated by the Wnt/β-catenin pathway and the significance of this regulation in cell metabolism and cell fate. This work was supported by the National Institutes of Health (NIH) (to J.R.), the Howard Hughes Medical Institute (HHMI) (to J.R.) and the Burroughs Wellcome Fund (BWF) (to L.C.R).
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".