Coordinated regulation of pH alkalinization by two transcription factors promotes fungal commensalism and pathogenicity
Bibliographic record
Abstract
As a clinically relevant opportunistic human fungal pathogen, Candida albicans is able to rapidly sense and adapt to changing microenvironments within the host, a process that is essential for its successful invasion and survival. Although studies have shown that the transcription factor Stp2 is the master regulator of environmental alkalinization, accumulating evidence supports a clear involvement of other participants in this adaptation process. Here, following a large-scale genetic screen, we identify the transcription factor Dal81 as an uncharacterized positive regulator of pH alkalinization in C. albicans. Dal81 influences the protein levels of Stp2. A mutant lacking DAL81 also fails to alkalinize both in vitro and in the phagolysosome, and this defective phenotype is further enhanced by deleting both factors in most cases. Notably, our results demonstrate that Dal81 physically interacts with Stp2 to co-regulate the expression of a broad set of downstream target genes related to metabolism of organic acids, oxoacids, carboxylic acids and amino acids. This coordinated regulation mode is required for the alkalinization process and plays a role in modulating commensalism and pathogenicity of C. albicans. Taken together, our findings elucidate the cooperative function of Dal81 with Stp2 in the nucleus to orchestrate the expression of downstream genes required for the survival and propagation of C. albicans in the host.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".