Cysteine Restriction-Specific Effects of Sulfur Amino Acid Restriction on Lipid Metabolism
Bibliographic record
Abstract
Summary Decreasing dietary intake of methionine exerts robust anti-adiposity effects in rodents but modest effects in humans. Since cysteine can be synthesized from methionine, animal diets are formulated by decreasing methionine and eliminating cysteine. Such diets exert both methionine restriction (MR) and cysteine restriction (CR), i.e., sulfur amino acid restriction (SAAR). Contrarily, human diets used in clinical studies did not eliminate cysteine and thus might have exerted only MR. Epidemiological studies positively correlate body adiposity with plasma cysteine but not with methionine, suggesting that CR, but not MR, is responsible for the antiadiposity effects of SAAR in rodents. Whether this is true, and if so, the underlying mechanisms are unknown. Using multiple diets with variable concentrations of methionine and cysteine, we demonstrate that the anti-adiposity effects of SAAR are due to CR. CR increased serinogenesis (serine biosynthesis from non-glucose substrates) by diverting substrates from glyceroneogenesis, essential for fatty acid/triglyceride cycling. Molecular data suggest that the CR results in glutathione depletion, which induces Nrf2 and downstream targets Phgdh (the serine biosynthetic enzyme) and Pepck-M. Using multiple mouse models, we show that the magnitude of SAAR-induced changes in molecular markers depends on dietary fat concentration (60 fat>10% fat), gender (males>females), and age-at-onset (young>adult). Our findings are translationally relevant as we found a negative correlation of plasma serine with triglycerides and metabolic syndrome criteria in a cross-sectional epidemiological study. SAAR-like diets with high polyunsaturated fatty acids increased plasma serine in a short-term human feeding study. Serinogenesis might be a potential target to correct hypertriglyceridemia.
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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) | 0.002 | 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".