Long-Range Ordering of Blunt-Ended DNA Tiles on Supported Lipid Bilayers
Bibliographic record
Abstract
Long-range ordering of DNA crossover tiles with blunt ends on lipid bilayers is investigated using atomic force microscopy. "Blunt-ended" tiles do not have single-stranded complementary ends, and thus instead of assembling via base-pairing, they can interact by π-stacking of their duplex ends. This work demonstrates that the balance of base π-stacking interactions between the ends of DNA duplexes, cholesterol-mediated DNA anchoring, and electrostatic DNA binding to supported lipid bilayers (SLBs) presents an opportunity to build dynamic materials with long-range order on a soft support. The tiles are shown to organize into novel tunable surface packing morphologies on the micrometer scale. This work focuses on three-point star (3PS) tiles that are either unmodified or modified with a cholesterol unit and investigates their interactions on supported lipid bilayers. On fluid bilayers, the cholesterol tiles form extended hexagonal arrays with few defects, while the unmodified tiles do not bind. In contrast, both modified and unmodified tiles bind to gel-phase bilayers and produce arrays of new organized morphologies. With increasing tile concentration, we observe a range of motifs, that progressively favor tile-tile packing over duplex-end π-stacking. These structures can selectively pattern domains of phase-separated lipid bilayers, and the patterning is also observed for four-arm cross-tiles. Dynamic blunt end contacts promote error correction and network reconfiguration to maximize favorable interactions with the substrate and are required for the observed tile organization. These results suggest that small blunt-ended tiles can be used as a platform to organize oligonucleotides, nanoparticles, and proteins into extensive networks at the interface with biologically relevant membrane systems or other soft surface materials for applications in cellular recognition, plasmonics, light harvesting, model systems for membrane protein assemblies, or analytical devices.
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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".