DNA Adsorption by ZnO Nanoparticles near Its Solubility Limit: Implications for DNA Fluorescence Quenching and DNAzyme Activity Assays
Bibliographic record
Abstract
Zinc oxide (ZnO) is a highly important material, and Zn(2+) is a key metal ion in biology. ZnO and Zn(2+) interconvert via dissolution and hydrolysis/condensation. In this work, we explore their interactions with DNA, which is important for biointerface, analytical, and bioinorganic chemistry. Fluorescently labeled DNA oligonucleotides were adsorbed by a low concentration (around 5 μg/mL) of ZnO nanoparticles, near the solubility limit. Right after mixing, fluorescence quenching occurred, indicating DNA adsorption. Then, fluorescence recovered, attributable to ZnO dissolution. The dissolution rate followed A5 > T5 > C5. Dissolution was slower with longer DNA. The adsorption affinity was also measured by a displacement assay to be G5 > C5 > T5 > A5, suggesting that tightly adsorbed DNA can retard ZnO dissolution. Electrostatic interactions are important for DNA adsorption because ZnO is positively charged at neutral pH, and a high salt concentration inhibits DNA adsorption. Next, in situ formation of ZnO from Zn(2+) was studied. First, titrating Zn(2+) into a fluorescently labeled oligonucleotide at pH 7.5 resulted in an abrupt fluorescence quenching beyond 0.2 mM Zn(2+). At pH 6, quenching occurred linearly with the Zn(2+) concentration, suggesting the effect of Zn(2+) precipitation at pH 7.5. Second, a Zn(2+)-dependent DNA-cleaving DNAzyme was studied. This DNAzyme was inhibited at higher than 2 mM Zn(2+), attributable to Zn(2+) precipitation and adsorption of the DNAzyme. This paper has established the interplay between DNA, Zn(2+), and ZnO. This understanding can avoid misinterpretation of DNA assay results and adds knowledge to DNA immobilization.
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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".