Evidence of an intracellular creatine-sensing mechanism that modulates creatine biosynthesis via AGAT expression in human HAP1 cells
Bibliographic record
Abstract
Cellular homeostasis of creatine (CT), integral part of the energy buffering and transducing system connecting intracellular sites of ATP production and utilization, comprises of mechanisms that increase CT, i.e., biosynthesis and cellular uptake, and CT-lowering processes, such as export and non-enzymatic conversion to creatinine. The biosynthesis of CT is controlled by negative feedback loop via suppression of the rate-limiting enzyme arginine:glycine amidinotransferase (AGAT). Although the regulatory mechanism involved is not well understood, AGAT suppression is successfully used in patients with guanidinoacetate methyltransferase (GAMT) deficiency to reduce the neurotoxic accumulation of the AGAT-mediated guanidinoacetate production by supplementing patients with CT. Utilizing the CT-dependent feedback loop for the upregulation of AGAT expression may well represent a therapeutic target for an additional CT deficiency syndrome, the CT transporter (CrT) defect, for which no effective treatment option is available so far. We have used CRISPR to tag the C-terminus of AGAT with a nanoluc luciferase (NLuc) reporter in HAP1 cells. A biphasic decay of AGAT-NLuc in response to increasing extracellular CT was observed, whereas the decrease in AGAT-NLuc expression was directly proportional to the rise in intracellular CT levels with an approximate IC50 of 1-2 mM. CRISPR generated HAP1 CrT null cells and HAP1 CrT null cells stably expressing a CrT-GFP fusion protein further demonstrated that the biphasic response to extracellular CT is mediated by a high-affinity (Km 9-10 µM) CrT dependent, saturable mechanism and a CrT independent, unsaturable uptake process. The direct response to intracellular CT suggests the existence of an intracellular CT sensing system enabling a dynamic cell response to changing CT concentration that is relevant for cellular CT homeostasis.
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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 | 0.001 |
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".