Conjugated Linoleic Acid Inhibits Hyphal Growth in Candida albicans by Modulating Ras1p Cellular Levels and Downregulating TEC1 Expression
Bibliographic record
Abstract
The polymorphic yeast Candida albicans exists in yeast and filamentous forms. Given that the morphogenetic switch coincides with the expression of many virulence factors, the yeast-to-hypha transition constitutes an attractive target for the development of new antifungal agents. Since an untapped therapeutic potential resides in small molecules that hinder C. albicans filamentation, we characterized the inhibitory effect of conjugated linoleic acid (CLA) on hyphal growth and addressed its mechanism of action. CLA inhibited hyphal growth in a dose-dependent fashion in both liquid and solid hypha-inducing media. The fatty acid blocked germ tube formation without affecting cellular growth rates. Global transcriptional profiling revealed that CLA downregulated the expression of hypha-specific genes and abrogated the induction of several regulators of hyphal growth, including TEC1, UME6, RFG1, and RAS1. However, neither UME6 nor RFG1 was necessary for CLA-mediated hyphal growth inhibition. Expression analysis showed that the downregulation of TEC1 expression levels by CLA depended on RAS1. In addition, while RAS1 transcript levels remained constant in CLA-treated cells, its protein levels declined with time. With the use of a strain expressing GFP-Ras1p, CLA treatment was also shown to affect Ras1p localization to the plasma membrane. These findings suggest that CLA inhibits hyphal growth by affecting the cellular localization of Ras1p and blocking the increase in RAS1 mRNA and protein levels. Combined, these effects should prevent the induction of the Ras1p signaling pathway. This study provides the biological and molecular explanations that underlie CLA's ability to inhibit hyphal growth in C. albicans.
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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".