Shaking Alone Induces De Novo Conversion of Recombinant Prion Proteins to β-Sheet Rich Oligomers and Fibrils
Bibliographic record
Abstract
The formation of β-sheet rich prion oligomers and fibrils from native prion protein (PrP) is thought to be a key step in the development of prion diseases. Many methods are available to convert recombinant prion protein into β-sheet rich fibrils using various chemical denaturants (urea, SDS, GdnHCl), high temperature, phospholipids, or mildly acidic conditions (pH 4). Many of these methods also require shaking or another form of agitation to complete the conversion process. We have identified that shaking alone causes the conversion of recombinant PrP to β-sheet rich oligomers and fibrils at near physiological pH (pH 5.5 to pH 6.2) and temperature. This conversion does not require any denaturant, detergent, or any other chemical cofactor. Interestingly, this conversion does not occur when the water-air interface is eliminated in the shaken sample. We have analyzed shaking-induced conversion using circular dichroism, resolution enhanced native acidic gel electrophoresis (RENAGE), electron microscopy, Fourier transform infrared spectroscopy, thioflavin T fluorescence and proteinase K resistance. Our results show that shaking causes the formation of β-sheet rich oligomers with a population distribution ranging from octamers to dodecamers and that further shaking causes a transition to β-sheet fibrils. In addition, we show that shaking-induced conversion occurs for a wide range of full-length and truncated constructs of mouse, hamster and cervid prion proteins. We propose that this method of conversion provides a robust, reproducible and easily accessible model for scrapie-like amyloid formation, allowing the generation of milligram quantities of physiologically stable β-sheet rich oligomers and fibrils. These results may also have interesting implications regarding our understanding of prion conversion and propagation both within the brain and via techniques such as protein misfolding cyclic amplification (PMCA) and quaking induced conversion (QuIC).
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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 | 0.001 |
| 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".