Entrapment of Fluorescent Signaling DNA Aptamers in Sol−Gel-Derived Silica
Bibliographic record
Abstract
We report on the first successful immobilization of a DNA aptamer, in particular, a fluorescence-signaling DNA aptamer, within a sol-gel-derived matrix. The specific aptamer examined in this study undergoes a structural switch in the presence of adenosine triphosphate (ATP) to release a dabcyl-labeled nucleotide strand (QDNA), which in turn relieves the quenching of a fluorescein label that is also present in the aptamer structure. It was demonstrated that aptamers containing a complementary QDNA strand along with either a short complimentary strand bearing fluorescein (tripartite structure) or a directly bound fluorescein moiety (bipartite structure) remained intact upon entrapment within biocompatible sol-gel derived materials and retained binding activity, structure-switching capabilities, and fluorescence signal generation that was selective and sensitive to ATP concentration. Studies were undertaken to evaluate the properties of the immobilized aptamers that were either in their native state or bound to streptavidin using a terminal biotin group on the aptamer, including response time, accessibility, and leaching. Furthermore, signaling abilities were optimized through evaluation of different QDNA constructs. These studies indicated that the aptamers remained in a state that was similar to solution, with moderate leaching, only minor decreases in accessibility to ATP, and an expected reduction in response time due to diffusional barriers to mass transport of the analyte through the silica matrix. Entrapment of the aptamer also resulted in protection of the DNA against degradation from nucleases, improving the potential for use of the aptamer for in vivo sensing. This work demonstrates that sol-gel-derived materials can be used to successfully immobilize and protect DNA-based biorecognition elements and, in particular, DNA aptamers, opening new possibilities for the development of DNA aptamer-based devices, such as affinity columns, microarrays, and fiber-optic 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".