A mitochondrial-targeted activity-based sensing probe for ratiometric imaging of formaldehyde reveals key regulators of the mitochondrial one-carbon pool
Bibliographic record
Abstract
Formaldehyde (FA) is both a highly reactive environmental genotoxin and an endogenously produced metabolite that functions as a signaling molecule and one-carbon (1C) store to regulate 1C metabolism and epigenetics in the cell. Owing to its signal-stress duality, cells have evolved multiple clearance mechanisms to maintain FA homeostasis, acting to avoid the established genotoxicity of FA while also redirecting FA-derived carbon units into the biosynthesis of essential nucleobases and amino acids. The highly compartmentalized nature of FA exposure, production, and regulation motivates the development of chemical tools that enable monitoring of transient FA fluxes with subcellular resolution. Here we report a mitochondrial-targeted, activity-based sensing probe for ratiometric FA detection, MitoRFAP-2, and apply this reagent to monitor endogenous mitochondrial sources and sinks of this 1C unit. We establish the utility of subcellular localization by showing that MitoRFAP-2 is sensitive enough to detect changes in mitochondrial FA pools with genetic and pharmacological modulation of enzymes involved in 1C and amino acid metabolism, including the pervasive, less active genetic mutant aldehyde dehydrogenase 2*2 (ALDH2*2), where previous, non-targeted versions of FA sensors are not. Finally, we used MitoRFAP-2 to comparatively profile basal levels of FA across a panel of breast cancer cell lines, finding that FA-dependent fluorescence correlates with expression levels of enzymes involved in 1C metabolism. By showcasing the ability of MitoRFAP-2 to identify new information on mitochondrial FA homeostasis, this work provides a starting point for the design of a broader range of chemical probes for detecting physiologically important aldehydes with subcellular resolution and a useful reagent for further studies of 1C biology.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".