Cross-Species and Cross-Polymorph Seeding of Lysozyme Amyloid Reveals a Dominant Polymorph
Bibliographic record
Abstract
The ability to self-propagate is one of the most intriguing characteristics of amyloid fibrils, and is a feature of great interest both to stopping unwanted pathological amyloid, and for engineering functional amyloid as a useful nanomaterial. The sequence and structural tolerances for amyloid seeding are not well understood, particularly concerning the propagation of distinct fibril morphologies (polymorphs) across species. This study examined the seeding and cross-seeding reactions between two unique fibril polymorphs, one long and flexible (formed at pH 2) and the other short and rigid (formed at pH 6.3), of human lysozyme and hen egg-white lysozyme. Both polymorphs could cross-seed aggregation across species, but this reaction was markedly reduced under physiological conditions. For both species, the pH 6.3 fibril polymorph was dominant, seeding fibril growth with a faster growth rate constant at pH 2 than the pH 2 polymorph. Based on fibrillation kinetics and fibril morphology, we found that the pH 2 polymorph was not able to faithfully replicate itself at pH 6.3. These results show that two distinct amyloid polymorphs are both capable of heterologous seeding across two species (human and hen) of lysozyme, but that the pH 6.3 polymorph is favored, regardless of the species, likely due to a lower energy barrier, or faster configurational diffusion, to accessing this particular misfolded form. These findings contribute to our better understanding of amyloid strain propagation across species barriers.
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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) | 0.000 | 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 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".