Signaling through Lrg1, Rho1 and Pkc1 Governs Candida albicans Morphogenesis in Response to Diverse Cues
Bibliographic record
Abstract
The capacity to transition between distinct morphological forms is a key virulence trait for diverse fungal pathogens. A poignant example of a leading opportunistic fungal pathogen of humans for which an environmentally responsive developmental program underpins virulence is Candida albicans. C. albicans mutants that are defective in the transition between yeast and filamentous forms typically have reduced virulence. Although many positive regulators of C. albicans filamentation have been defined, there are fewer negative regulators that have been implicated in repression of filamentation in the absence of inducing cues. To discover novel negative regulators of filamentation, we screened a collection of 1,248 C. albicans homozygous transposon insertion mutants to identify those that were filamentous in the absence of inducing cues. We identified the Rho1 GAP Lrg1, which represses filamentous growth by stimulating Rho1 GTPase activity and converting Rho1 to its inactive, GDP-bound form. Deletion of LRG1 or introduction of a RHO1 mutation that locks Rho1 in constitutively active, GTP-bound state, leads to filamentation in the absence of inducing cues. Deletion of the Rho1 downstream effector PKC1 results in defective filamentation in response to diverse host-relevant inducing cues, including serum. We further established that Pkc1 is not required to sense filament-inducing cues, but its kinase activity is critical for the initiation of filamentous growth. Our genetic analyses revealed that Pkc1 regulates filamentation independent of the canonical MAP kinase cascade. Further, although Ras1 activation is not impaired in a pkc1Δ/pkc1Δ mutant, adenylyl cyclase activity is reduced, consistent with a model in which Pkc1 functions in parallel with Ras1 in regulating Cyr1 activation. Thus, our findings delineate a signaling pathway comprised of Lrg1, Rho1 and Pkc1 with a core role in C. albicans morphogenesis, and illuminate functional relationships that govern activation of a central transducer of signals that control environmental response and virulence programs.
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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".