Disulfide-crosslink scanning reveals prion–induced conformational changes and prion strain–specific structures of the pathological prion protein PrPSc
Bibliographic record
Abstract
Prions are composed solely of the pathological isoform (PrP Sc ) of the normal cellular prion protein (PrP C ). Identification of different PrP Sc structures is crucially important for understanding prion biology because the pathogenic properties of prions are hypothesized to be encoded in the structures of PrP Sc . However, these structures remain yet to be identified, because of the incompatibility of PrP Sc with conventional high-resolution structural analysis methods. Previously, we reported that the region between the first and the second α-helix (H1∼H2) of PrP C might cooperate with the more C-terminal side region for efficient interactions with PrP Sc . From this starting point, we created a series of PrP variants with two cysteine substitutions (C;C-PrP) forming a disulfide-crosslink between H1∼H2 and the distal region of the third helix (Ctrm). We then assessed the conversion capabilities of the C;C-PrP variants in N2a cells infected with mouse-adapted scrapie prions (22L-ScN2a). Specifically, Cys substitutions at residues 165, 166, or 168 in H1∼H2 were combined with cysteine scanning along Ctrm residues 220–229. We found that C;C-PrPs are expressed normally with glycosylation patterns and subcellular localization similar to WT PrP, albeit differing in expression levels. Interestingly, some C;C-PrPs converted to protease-resistant isoforms in the 22L-ScN2a cells, but not in Fukuoka1 prion-infected cells. Crosslink patterns of convertible C;C-PrPs indicated a positional change of H1∼H2 toward Ctrm in PrP Sc –induced conformational conversion. Given the properties of the C;C-PrPs reported here, we propose that these PrP variants may be useful tools for investigating prion strain–specific structures and structure–phenotype relationships of PrP Sc .
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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".