An “Exacerbate-reverse” Strategy in Yeast Identifies Histone Deacetylase Inhibition as a Correction for Cholesterol and Sphingolipid Transport Defects in Human Niemann-Pick Type C Disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Niemann-Pick type C (NP-C) disease is a fatal lysosomal lipid storage disorder for which no effective therapy exists. A genome-wide, conditional synthetic lethality screen was performed using the yeast model of NP-C disease during anaerobiosis, an auxotrophic condition that requires yeast to utilize exogenous sterol. We identified 12 pathways and 13 genes as modifiers of the absence of the yeast NPC1 ortholog (NCR1) and quantified the impact of loss of these genes on sterol metabolism in ncr1Δ strains grown under viable aerobic conditions. Deletion of components of the yeast NuA4 histone acetyltransferase complex in ncr1Δ strains conferred anaerobic inviability and accumulation of multiple sterol intermediates. Thus, we hypothesize an imbalance in histone acetylation in human NP-C disease. Accordingly, we show that the majority of the 11 histone deacetylase (HDAC) genes are transcriptionally up-regulated in three genetically distinct fibroblast lines derived from patients with NP-C disease. A clinically approved HDAC inhibitor (suberoylanilide hydroxamic acid) reverses the dysregulation of the majority of the HDAC genes. Consequently, three key cellular diagnostic criteria of NP-C disease are dramatically ameliorated as follows: lysosomal accumulation of both cholesterol and sphingolipids and defective esterification of LDL-derived cholesterol. These data suggest HDAC inhibition as a candidate therapy for NP-C disease. We conclude that pathways that exacerbate lethality in a model organism can be reversed in human cells as a novel therapeutic strategy. This "exacerbate-reverse" approach can potentially be utilized in any model organism for any disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it