Characterization of the Reconstituted γ-Secretase Complex from Sf9 Cells Co-Expressing Presenilin 1, Nacastrin, aph-1a, and pen-2
Bibliographic record
Abstract
Gamma-secretase catalyzes the proteolytic processing of a number of integral membrane proteins, including amyloid precursor protein (APP) and Notch. The native gamma-secretase is a heterogeneous population of large membrane protein complexes containing presenilin 1 (PS1) or presenilin 2 (PS2), aph-1a or aph-1b, nicastrin, and pen-2. Here we report the reconstitution of a gamma-secretase complex in Sf9 cells by co-infection with baculoviruses carrying the PS1, nicastrin, pen-2, and aph-1a genes. The reconstituted enzyme processes C99 and the Notch-like substrate N160 and displays the characteristic features of gamma-secretase in terms of sensitivity to a gamma-secretase inhibitor, upregulation of Abeta42 production by a familial Alzheimer's disease (FAD) mutation in the APP gene, and downregulation of Notch processing by PS1 FAD mutations. However, the ratio of Abeta42:Abeta40 production by the reconstituted gamma-secretase is significantly higher than that of the native enzyme from 293 cells. Unlike in mammalian cells where PS1 FAD mutations cause an increase in Abeta42 production, PS1 FAD missense mutations in the reconstitution system alter the cleavage sites in the C99 substrate without changing the Abeta42:Abeta40 ratio. In addition, PS1DeltaE9 is a loss-of-function mutation in both C99 and N160 processing. Reconstitution of gamma-secretase provides a homogeneous system for studying the individual gamma-secretase complexes and their roles in Abeta production, Notch processing and AD pathogenesis. These studies may provide important insight into the development of a new generation of selective gamma-secretase inhibitors with an improved side effect profile.
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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 | 0.000 | 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 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".