Fibril-mediated oligomerization of pilin-derived protein nanotubes
Bibliographic record
Abstract
BACKGROUND: Self-assembling protein nanotubes (PNTs) are an intriguing alternative to carbon nanotubes for applications in bionanotechnology, in part due to greater inherent biocompatibility. The type IV pilus of the gram negative bacteria Pseudomonas aeruginosa is a protein-based fibre composed of a single subunit, the type IV pilin. Engineered pilin monomers from P. aeruginosa strain K122-4 (ΔK122) have been shown to oligomerize into PNTs both in solution and at surfaces. In order to fully exploit PNTs in bionanotechonological settings, an in-depth understanding of their assembly, physical characteristics and robustness, both in solution and when constrained to surfaces, is required. RESULTS: This study details the effectiveness of multiple initiators of ΔK122-derived PNT oligomerization and characterize the formation of PNTs in solution. The optimal initiator for the oligomerization of ΔK122 in solution was observed to be 2-methyl-2,4-pentanediol (MPD). Conversely, larger PEG molecules do not trigger oligomerization. Multi-angle light scattering analysis indicates that the pilin protein exists in a monomer-dimer equilibrium in solution, and that an intermediate species forms within three hours that then coalesces over time into high molecular weight PNTs. Transmission Electron Microscopic analysis was used to observe the formation of oligomerized ΔK122 fibrils prior to assembly into full-length PNTs. CONCLUSIONS: The oligomerization of ΔK122 pilin derived PNTs is a fibril mediated process. The optimal trigger for PNT oligomerization in solution is MPD, and the observation that PEGs do not induce oligomerization may enable the oligomerization of pilin-derived PNTs on PEG-functionalized surfaces for implantable bionanodevices.
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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".