Diabetes Induces Lysine Acetylation of Intermediary Metabolism Enzymes in the Kidney
Bibliographic record
Abstract
Cells in which insulin is not required for glucose uptake are susceptible to the long-term complications of diabetes. Even in these tissues, however, the major perturbations that would otherwise be engendered by the greatly increased intracellular glucose concentration are mollified by adaptive changes in the enzymes of intermediary metabolism. These include allosteric regulation, product inhibition, and covalent modification as well as alterations in gene transcription. More recently, advances in proteomic technology have shown that reversible acetylation of the ε-amino group of lysine provides an additional means of modulating protein function and, in particular, enzyme activity. Here, we explored the extent of protein acetylation in an organ susceptible to the long-term complications of diabetes, examining the kidneys of rats with streptozotocin-induced diabetes and kidney cells exposed to high glucose. Using high-resolution mass spectrometry coupled with immunoaffinity enrichment, we identified 47 lysine-acetylated proteins in the kidneys of diabetic rats compared with 11 in control kidneys. Bioinformatic interrogation of the acetylome from diabetic animals showed a predominance of metabolic pathway involvement including the citrate acid cycle, glycolysis/gluconeogenesis, and metabolism of branched chain amino acids. Increased lysine acetylation was also noted in mesangial and tubular cells exposed to 25 mmol/L compared with 5.6 mmol/L glucose. These findings highlight acetylation as a posttranslational modification affecting numerous proteins. Current drug discovery efforts to develop small molecule inhibitors and activators of various lysine acetylases and deacetylases offer a new potential strategy to reduce the likelihood of diabetes complications.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".