Polyglutamine toxicity in yeast uncovers phenotypic variations between different fluorescent protein fusions
Bibliographic record
Abstract
The palette of fluorescent proteins (FPs) available for live-cell imaging contains proteins that strongly differ in their biophysical properties. FPs cannot be assumed to be equivalent and in certain cases could significantly perturb the behavior of fluorescent reporters. We employed Saccharomyces cerevisiae to comprehensively study the impact of FPs on the toxicity of polyglutamine (polyQ) expansion proteins associated with Huntington's disease. The toxicity of polyQ fusion constructs is highly dependent on the sequences flanking the polyQ repeats. Thus, they represent a powerful tool to study the impact of fluorescent fusion partners. We observed significant differences on polyQ aggregation and toxicity between commonly used FPs. We generated a novel series of vectors with latest yeast-optimized FPs for investigation of Htt toxicity, including a newly optimized blue FP for expression in yeast. Our study highlights the importance of carefully choosing the optimal FPs when designing tagging strategies.
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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".