Nucleic Acid-Passivated Semiconductor Nanocrystals: Biomolecular Templating of Form and Function
Bibliographic record
Abstract
Bright, photostable luminescent labels are powerful tools for the in vitro and in vivo imaging of biological events. Semiconductor nanocrystals have emerged as attractive alternatives to commonly used organic lumophores because of their high quantum yields and the spectral tunability that can be achieved through synthetic control. Although conventional synthetic methods generally yield high-quality nanocrystals with excellent optical properties for biological imaging, ligand exchange and biological conjugation are necessary to make nanocrystals biocompatible and biospecific. These steps can substantially deteriorate the optical characteristics of these nanocrystals. Moreover, the complexity of multistep nanocrystal synthesis, typically requiring inert and anhydrous conditions, prohibits many end users of these lumiphores from generating their own custom materials. We sought to streamline semiconductor nanocrystal synthesis and develop synthetic routes that would be accessible to scientists from all disciplines. In search of such an approach, we turned to nucleic acids as a programmable and versatile ligand set and found that these biomolecules are indeed appropriate for biocompatible semiconductor nanocrystals preparation. In this Account, we summarize our work on nucleic acids-programmed nanocrystal synthesis that has resulted in the successful development of a one-step synthesis of biofunctionalized nanocrystals in aqueous solution. We first discuss results obtained with nucleotide-capped cadmium and lead chalcogenide-based nanocrystals that served to guide further investigation of polynucleotide-assisted synthesis. We investigated the roles of individual nucleobases and their structures in passivation of the surfaces of nanocrystals and modulating morphology and optical characteristics. The nucleic acid structures and sequences and the reaction conditions greatly influence the nanocrystals' optical properties and morphologies. Moreover, studies using live cells reveal low toxicity and rapid uptake of DNA-passivated CdS nanocrystals, demonstrating their suitability for bioimaging. Finally, we describe a new approach that leads to the production of biofunctionalized, DNA-capped nanocrystals in a single step. Chimeric DNA molecules enable this strategy, providing both a domain for nanocrystal passivation and a domain for biomolecule recognition. Nanocrystals synthesized using this approach possess good spectral characteristics as well as high specificity to cognate DNA, protein, and cancer cell targets. Overall, this approach could make nanocrystal lumiphores more readily accessible to researchers working in the biological sciences.
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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 | 0.000 | 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) | 0.001 | 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".