In Situ Visualizing the Recognition Between Proteins and Platinum-Damaged DNA in Single-Cells by Correlated Optical and Secondary Ion Mass Spectrometric Imaging
Bibliographic record
Abstract
In situ visualization of the recognition and interactions between proteins and drug damaged DNA at single cell level is highly important for understanding the molecular mechanism of action of DNA targeting drugs, yet a great challenge. We report herein a novel approach, termed as correlated optical and secondary ion mass spectrometric imaging (COSIMSi), to explore the recognition between proteins and cisplatin-damaged DNA in single cells. Genetically encoded EYFP-fused HMGB1, an in vitro well-known specific binder of cisplatin-damaged DNA, dye-stained DNA, and platinum were mapped by LSCM and ToF-SIMS imaging, respectively. The LSCM and SIMS images were aligned with aiding of an addressable silicon wafer to generate fused images, in which the co-localization of the fluorescent and MS signals indicated the formation of HMGB1-Pt-DNA ternary complexes in a dose- and time-dependent manner. In contrast, COSIMSi results showed that little HMGB1(F37A)-Pt-DNA complex was produced under the same conditions. Moreover, we demonstrated for the first time that cisplatin lesions on DNA prevented DNA-binding proteins Smad3 and Smad7 from interacting with DNA. These results verify that the COSIMSi is an effective and straightforward tool for in situ visualization of recognition and interactions between proteins and specific damaged DNA in single cells.
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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 | 0.001 |
| 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) | 0.000 | 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".