Motif affinity and mass spectrometry proteomic approach for the discovery of cellular AMPK targets: Identification of mitochondrial fission factor as a new AMPK substrate
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AMP-activated protein kinase (AMPK) is a key cellular energy sensor and regulator of metabolic homeostasis. Although it is best known for its effects on carbohydrate and lipid metabolism, AMPK is implicated in diverse cellular processes, including mitochondrial biogenesis, autophagy, and cell growth and proliferation. To further our understanding of energy homeostasis through AMPK-dependent processes, the design and application of approaches to identify and characterise novel AMPK substrates are invaluable. Here, we report an affinity proteomicstrategy for the discovery and validation of AMPK targets using an antibody to isolate proteins containing the phospho-AMPK substrate recognition motif from hepatocytes that had been treated with pharmacological AMPK activators. We identified 57 proteins that were uniquely enriched in the activator-treated hepatocytes, but were absent in hepatocytes lacking AMPK. We focused on two candidates, cingulin and mitochondrial fission factor (MFF), and further characterised/validated them as AMPK-dependent targets by immunoblotting with phosphorylation site-specific antibodies. A small-molecule AMPK activator caused transient phosphorylation of endogenous cingulin at S137 in intestinal Caco2 cells. Multiple splice-variants of MFF appear to express in hepatocytes and we identified a common AMPK-dependent phospho-site (S129) in all the 3 predominant variants spanning the mass range and a short variant-specific site (S146). Collectively, our proteomic-based approach using a phospho-AMPK substrate antibody in combination with genetic models and selective AMPK activators will provide a powerful and reliable platform for identifying novel AMPK-dependent cellular targets.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it