The l-isoaspartate modification within protein fragments in the aging lens can promote protein aggregation
Bibliographic record
Abstract
Transparency in the lens is accomplished by the dense packing and short-range order interactions of the crystallin proteins in fiber cells lacking organelles. These features are accompanied by a lack of protein turnover, leaving lens proteins susceptible to a number of damaging modifications and aggregation. The loss of lens transparency is attributed in part to such aggregation during aging. Among the damaging post-translational modifications that accumulate in long-lived proteins, isomerization at aspartate residues has been shown to be extensive throughout the crystallins. In this study of the human lens, we localize the accumulation of l-isoaspartate within water-soluble protein extracts primarily to crystallin peptides in high-molecular weight aggregates and show with MS that these peptides are from a variety of crystallins. To investigate the consequences of aspartate isomerization, we investigated two αA crystallin peptides 52 LFRTVLDSGISEVR 65 and 89 VQDDFVEIH 98 , identified within this study, with the l-isoaspartate modification introduced at Asp 58 and Asp 91 , respectively. Importantly, whereas both peptides modestly increase protein precipitation, the native 52 LFRTVLDSGISEVR 65 peptide shows higher aggregation propensity. In contrast, the introduction of l-isoaspartate within a previously identified anti-chaperone peptide from water-insoluble aggregates, αA crystallin 66 SDRDKFVIFL(isoAsp)VKHF 80 , results in enhanced amyloid formation in vitro . The modification of this peptide also increases aggregation of the lens chaperone αB crystallin. These findings may represent multiple pathways within the lens wherein the isomerization of aspartate residues in crystallin peptides differentially results in peptides associating with water-soluble or water-insoluble aggregates. Here the eye lens serves as a model for the cleavage and modification of long-lived proteins within other aging tissues.
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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) | 0.001 | 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".