An Activity-Based Methionine Bioconjugation Approach to Developing Proximity-Activated Imaging Reporters
Bibliographic record
Abstract
Chemical probes that report on protein activity, rather than protein abundance, with spatial and temporal resolution can enable studies of their native function in biological contexts as well as provide opportunities for developing new types of biochemical reporters. Here we present a sensing platform, termed proximity-activated imaging reporter (PAIR), which combines activity-based methionine bioconjugation and antibody labeling with proximity-dependent oligonucleotide-based amplification to monitor dynamic changes of a given analyte in cells and animals through context-dependent methionine labeling of specific protein targets. We establish this PAIR method to develop sensors for imaging reactive oxygen species (ROS) and calcium ions through oxaziridine-directed labeling of reactive methionine residues on β-actin and calmodulin (CaM), respectively, where the extent of methionine bioconjugation on these protein targets can serve as an indicator of oxidative stress or calcium status. In particular, application of PAIR to activity-based CaM detection provides a method for imaging integrated calcium activity in both in vitro cell and in vivo zebrafish models. By relying on native protein biochemistry, PAIR enables redox and metal imaging without introduction of external small-molecules or genetically encoded indicators that can potentially buffer the natural/existing pools. This approach can be potentially generalized to target a broader range of analytes by pairing appropriate activity-based protein probes with protein detection reagents in a proximity-driven manner, providing a starting point not only for designing new sensors but also for monitoring endogenous activity of specific protein targets in biological specimens with spatial and temporal fidelity.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 0.001 |
| 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".