Split trehalase as a versatile reporter for a wide range of biological analytes
Bibliographic record
Abstract
In health care, biosensors are envisioned as universal diagnostic devices with AAAA characteristics (i.e., available for anything, anywhere, anytime, to anyone). Despite numerous attempts to develop such a diagnostic device, none have managed to fulfill all four criteria and be commercialized. Glucometers, the most successful class of biosensor currently marketed monitor blood glucose concentrations. Their performance in clinical samples, including sensitivity and specificity, has been optimized and they are small and relatively inexpensive. We aimed to develop a technology that uses this existing biosensor, but adds versatility in detection of a wide range of analytes. Herein, we report the periplasmic trehalase of E. coli as a novel split enzyme reporter capable of converting a wide variety of analytes into glucose. Conditional complementation of trehalase fragments induced by detection of analytes, resulting in trehalose hydrolysis and glucose production, was used to detect antibodies and bacterial cells. We also demonstrated retention of split TreA activity in undiluted clinical samples. In conclusion, a trehalase-based biosensor platform offers a versatile and convenient method for point-of-care applications as it does not require sample preparation or handling and can be integrated with existing glucometers or sensors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".