High-Performance Intensiometric Direct- and Inverse-Response Genetically Encoded Biosensors for Citrate
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Motivated by the growing recognition of citrate as a central metabolite in a variety of biological processes associated with healthy and diseased cellular states, we have developed a series of high-performance genetically encoded citrate biosensors suitable for imaging of citrate concentrations in mammalian cells. The design of these biosensors was guided by structural studies of the citrate-responsive sensor histidine kinase and took advantage of the same conformational changes proposed to propagate from the binding domain to the catalytic domain. Following extensive engineering based on a combination of structure guided mutagenesis and directed evolution, we produced an inverse-response biosensor (Δ F / F min ≈ 18) designated Citroff1 and a direct-response biosensor (Δ F / F min ≈ 9) designated Citron1. We report the X-ray crystal structure of Citron1 and demonstrate the utility of both biosensors for qualitative and quantitative imaging of steady-state and pharmacologically perturbed citrate concentrations in live cells.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".