An Activity-Based Sensing Approach to Multiplex Mapping of Labile Copper Pools by Stimulated Raman Scattering
Bibliographic record
Abstract
Molecular imaging with analyte-responsive probes offers a powerful chemical approach to studying biological processes. Many reagents for bioimaging employ a fluorescence readout, but the relatively broad emission bands of this modality and the need to alter the chemical structure of the fluorophore for different signal colors can potentially limit multiplex imaging. Here, we report a generalizable approach to multiplex analyte imaging by leveraging the comparably narrow spectral signatures of stimulated Raman scattering (SRS) in activity-based sensing (ABS) mode. We illustrate this concept with two copper Raman probes (CRPs), CRP2181 and CRP2153.2, that react selectively with loosely bound Cu(I/II) and Cu(II) ions, respectively, termed the labile copper pool, through copper-directed acyl imidazole (CDAI) chemistry. These reagents label proximal proteins in a copper-dependent manner using a dye scaffold bearing a 13 C≡N or 13 C≡ 15 N isotopic SRS tag with nearly identical physiochemical properties in terms of shape and size. SRS imaging with the CRP reagents enables duplex monitoring of changes in intracellular labile Cu(I) and Cu(II) pools upon exogenous copper supplementation or copper depletion or genetic perturbations to copper transport proteins. Moreover, CRP imaging reveals reciprocal increases in labile Cu(II) pools upon decreases in activity of the antioxidant response nuclear factor-erythroid 2-related factor 2 (NRF2) in cellular models of lung adenocarcinoma. By showcasing the use of narrow-bandwidth ABS probes for multiplex imaging of copper pools in different oxidation states and identifying alterations in labile metal nutrient pools in cancer, this work establishes a foundation for broader SRS applications in analyte-responsive imaging in biological systems.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".