Chemical Genetic Profiling and Characterization of Small-molecule Compounds That Affect the Biosynthesis of Unsaturated Fatty Acids in Candida albicans
Bibliographic record
Abstract
The balance between saturated and unsaturated fatty acids plays a crucial role in determining the membrane fluidity. In the diploid fungal pathogen Candida albicans, the gene for fatty acid Delta9 desaturase, OLE1, is essential for viability. Using a reverse genetic approach, termed the fitness test, we identified a group of structurally related synthetic compounds that induce specific hypersensitivity of the OLE1(+/-) strain. Genetic repression of OLE1 and chemical inhibition by two selected compounds, ECC145 and ECC188, resulted in a marked decrease in the total unsaturated fatty acids and impaired hyphal development. The resulting auxotroph of both was suppressed by the exogenous monounsaturated fatty acids (16:1Delta9 and 18:1Delta9). These correlations suggest that both compounds affect the level of unsaturated fatty acids, likely by impairing Ole1p directly or indirectly. However, the residual levels of monounsaturated fatty acids (MUFAs) resulted from chemical inhibition were significantly higher than OLE1 repression, indicating even partial inhibition of MUFAs is sufficient to stop cellular proliferation. Although the essentiality of OLE1 was suppressed by MUFAs in vitro, we demonstrated that it was required for virulence in a murine model of systemic candidiasis even when the animals were supplemented with a high fat diet. Thus, the fungal fatty acid desaturase is an attractive antifungal drug target. Taking advantage of the inhibitors and the relevant conditional shut-off strains, we validated several chemical genetic interactions observed in the fitness test profiles that reveal novel genetic interactions between OLE1/unsaturated fatty acids and other cellular processes.
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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 | 0.001 | 0.001 |
| 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".