Synthesis and application of a photocaged-l-lactate for studying the biological roles of l-lactate
Bibliographic record
Abstract
l-Lactate, once considered a metabolic waste product of glycolysis, is now recognized as a vitally important metabolite and signaling molecule in multiple biological pathways. However, exploring l-lactate’s emerging intra- and extra-cellular roles is hindered by a lack of tools to perturb l-lactate concentration intracellularly and extracellularly. Photocaged compounds are a powerful way to introduce bioactive molecules with spatiotemporal precision using illumination. Here, we report the development of a photocaged derivative of l-lactate, 4-methoxy-7-nitroindolinyl-l-lactate (MNI-l-lac), that releases l-lactate upon illumination. We validated MNI-l-lac in cell culture by demonstrating that the photorelease of l-lactate elicits a response from genetically encoded extra- and intracellular l-lactate biosensors (eLACCO1, eLACCO2.1, R-iLACCO1.2). To demonstrate the utility of MNI-l-lac, we employed the photorelease of l-lactate to activate G protein-coupled receptor 81 (GPR81), as revealed by the inhibition of adenylyl cyclase activity and concomitant decrease of cAMP. These results indicate that MNI-l-lac may be useful for perturbing the concentration of endogenous l-lactate in order to investigate l-lactate’s roles in metabolic and signaling pathways. l-Lactate is a product of glycolysis as well as a signaling molecule in multiple biological pathways, however, its biological role is not well-studied due to a lack of tools to perturb l-lactate concentration. Here, the authors synthesize a 4-methoxy-7-nitroindolinyl-l-lactate that can release l-lactate upon illumination and perturb the concentration of endogenous l-lactate.
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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) | 0.001 | 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".