Differential utilization of vitamin B12-dependent and independent pathways for propionate metabolism across human cells
Bibliographic record
Abstract
Propionic acid links the oxidation of branched-chain amino acids and odd-chain fatty acids to the TCA cycle. Gut microbes ferment complex fiber remnants, generating high concentrations of short chain fatty acids, acetate, propionate and butyrate, which are shared with the host as fuel sources. Analysis of vitamin B 12 -dependent propionate utilization in skin biopsy samples has been used to characterize and diagnose underlying inborn errors of cobalamin (or B 12 ) metabolism. In these cells, the B 12 -dependent enzyme, methylmalonyl-CoA mutase (MMUT), plays a central role in funneling propionate to the TCA cycle intermediate, succinate. Our understanding of the fate of propionate in other cell types, specifically, the involvement of the β-oxidation-like and methylcitrate pathways, is limited. In this study, we have used [ 14 C]-propionate tracing in combination with genetic ablation or inhibition of MMUT, to reveal the differential utilization of the B 12 -dependent and independent pathways for propionate metabolism in fibroblast versus colon cell lines. We demonstrate that itaconate can be used as a tool to investigate MMUT-dependent propionate metabolism in cultured cell lines. While MMUT gates the entry of propionate carbons into the TCA cycle in fibroblasts, colon-derived cell lines exhibit a quantitatively significant or exclusive reliance on the β-oxidation-like pathway. Lipidomics and metabolomics analyses reveal that propionate elicits pleiotropic changes, including an increase in odd-chain glycerophospholipids, and perturbations in the purine nucleotide cycle and arginine/nitric oxide metabolism. The metabolic rationale and the regulatory mechanisms underlying the differential reliance on propionate utilization pathways at a cellular, and possibly tissue level, warrant further elucidation.
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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) | 0.002 | 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".