Normal Adaptation of Candida albicans to the Murine Gastrointestinal Tract Requires Efg1p-Dependent Regulation of Metabolic and Host Defense Genes
Bibliographic record
Abstract
Although gastrointestinal colonization by the opportunistic fungal pathogen Candida albicans is generally benign, severe systemic infections are thought to arise due to escape of commensal C. albicans from the gastrointestinal (GI) tract. The C. albicans transcription factor Efg1p is a major regulator of GI colonization, hyphal morphogenesis, and virulence. The goals of this study were to identify the Efg1p regulon during GI tract colonization and to compare C. albicans gene expression during colonization of different organs of the GI tract. Our results identified significant differences in gene expression between cells colonizing the cecum and ileum. During colonization, efg1(-) null mutant cells expressed higher levels of genes involved in lipid catabolism, carnitine biosynthesis, and carnitine utilization than did colonizing wild-type (WT) cells. In addition, during laboratory growth, efg1(-) null mutant cells grew to a higher density than WT cells. The efg1(-) null mutant grew in depleted medium, while WT cells could grow only if the depleted medium was supplemented with carnitine, a compound that promotes the metabolism of fatty acids. Altered gene expression and altered growth capability support the ability of efg1(-) cells to hypercolonize naïve mice. Also, Efg1p was shown to be important for transcriptional responses to the stresses present in the cecum environment. For example, during colonization, SOD5, encoding a superoxide dismutase, was highly upregulated in an Efg1p-dependent manner. Ectopic expression of SOD5 in an efg1(-) null mutant increased the fitness of the efg1(-) null mutant cells during colonization. These data show that EFG1 is an important regulator of GI colonization.
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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 | 0.001 |
| 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".