A recombinant chimeric spider pyriform-aciniform silk with highly tunable mechanical performance
Bibliographic record
Abstract
Spider silks are natural protein-based biomaterials which are renowned for their mechanical properties and hold great promise for applications ranging from high-performance textiles to the regenerative medicine. While some spiders can produce several different types of silks, most spider silk types – including pyriform and aciniform silks – are relatively unstudied. Pyriform and aciniform silks have distinct mechanical behavior and physicochemical properties, with materials produced using combinations of these silks currently unexplored. Here, we introduce an engineered chimeric fusion protein consisting of two repeat units of pyriform (Py) silk followed by two repeat units of aciniform (W) silks named as Py2W2. This recombinant ∼86.5 kDa protein is amenable to expression and purification from Escherichia coli and exhibits high α-helicity in a fluorinated acid- and alcohol-based solution used to form a dope for wet-spinning. Wet-spinning enables continuous fiber production and post-spin stretching of the wet-spun fibers in air or following submersion in water or ethanol leads to increases in optical anisotropy, consistent with increased molecular alignment along the fiber axis. Mechanical properties of the fibers vary as a function of post-spin stretching condition, with the highest extensibility and strength observed in air-stretched and ethanol-treated fibers, respectively, with mechanics being superior to fibers spun from either constituent protein alone. Notably, the maximum extensibility obtained (∼157 ± 38%) is of the same magnitude reported natural flagelliform silks, the class of spider silk most associated with being stretchable. Interestingly, Py2W2 is also water-compatible, unlike its constituent Py2. Fiber-state secondary structure correlates well with the observed mechanical properties, with depleted α-helicity and increased β-sheet content in cases of increased strength. Py2W2 fibers thus provide enhanced materials behavior in terms of their mechanics, tunability, and fiber properties, providing new directions for design and development of biomaterials suitable and tunable for disparate applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".