Optimizing and Evaluating Hand-drawing and Wet-spinning for Recombinant Spider Silk Fiber Production
Bibliographic record
Abstract
Spider silks are renowned for their mechanical properties, with hallmark high strength, high extensibility, or a combination of these leading to high toughness. A typical female orb-weaving spider produces seven different types of silk, each typically spun from type-specific protein(s) and mechanically tailored for a distinct survival function. Recombinant spider silk production provides a promising route to obtain these materials, circumventing challenges in obtaining large quantities of natural silks and providing advantages in allowing for protein customization, for example, through site-directed mutagenesis or fusion protein construction. In the presented protocol, we outline a methodology for evaluating protein suitability for spinning through both hand-drawing and wet-spinning approaches. Starting with a suitably purified lyophilized protein powder, methods for optimizing the initial solubilized protein state to provide a high-concentration "spinning dope" state are detailed. Next, hand-drawing and wet-spinning approaches are compared, including a discussion on methods to modulate fiber behavior using a post-spin draw as part of the spinning process. A typical workflow to characterize the resulting silk fibers and make a decision on which spinning conditions are most likely to be fruitful is then detailed, including optical microscopy to evaluate fiber diameter and its uniformity; polarized light microscopy to estimate the degree of (supra)molecular alignment being achieved within the fiber; tensile testing to evaluate strength, extensibility, Young's modulus, and toughness; and Fourier transform infrared (FTIR) spectromicroscopy to evaluate protein secondary structuring within the fiber. This protocol has proven suitable for several different recombinant spider silk proteins based on repetitive and non-repetitive domains of aciniform (wrapping) silk; pyriform silk; and fusion proteins comprising aciniform, pyriform, and/or major ampullate (dragline) silk. Broader applicability is provided through several highlighted steps at which conditions and parameters may be varied to suit the behavior of an individual protein and to achieve differences in functional outcome.
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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 | 0.001 | 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".